{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 一、国内疫情数据分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##1.国内每日疫情数据分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>累积确诊</th>\n",
       "      <th>疑似病例</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>重症</th>\n",
       "      <th>输入病例</th>\n",
       "      <th>死亡率</th>\n",
       "      <th>治愈率</th>\n",
       "      <th>无症状感染</th>\n",
       "      <th>日期</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>01/13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>01/14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>12.2</td>\n",
       "      <td>0</td>\n",
       "      <td>01/15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>17.8</td>\n",
       "      <td>0</td>\n",
       "      <td>01/16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>19.4</td>\n",
       "      <td>0</td>\n",
       "      <td>01/17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>198</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>8.6</td>\n",
       "      <td>0</td>\n",
       "      <td>01/18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>275</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0</td>\n",
       "      <td>01/19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>291</td>\n",
       "      <td>54</td>\n",
       "      <td>6</td>\n",
       "      <td>25</td>\n",
       "      <td>291</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>8.6</td>\n",
       "      <td>0</td>\n",
       "      <td>01/20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>440</td>\n",
       "      <td>37</td>\n",
       "      <td>9</td>\n",
       "      <td>25</td>\n",
       "      <td>431</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>0</td>\n",
       "      <td>01/21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>574</td>\n",
       "      <td>393</td>\n",
       "      <td>17</td>\n",
       "      <td>25</td>\n",
       "      <td>557</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>0</td>\n",
       "      <td>01/22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>835</td>\n",
       "      <td>1072</td>\n",
       "      <td>25</td>\n",
       "      <td>34</td>\n",
       "      <td>776</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>0</td>\n",
       "      <td>01/23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1297</td>\n",
       "      <td>1965</td>\n",
       "      <td>41</td>\n",
       "      <td>38</td>\n",
       "      <td>1218</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0</td>\n",
       "      <td>01/24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1985</td>\n",
       "      <td>2684</td>\n",
       "      <td>56</td>\n",
       "      <td>49</td>\n",
       "      <td>1880</td>\n",
       "      <td>324</td>\n",
       "      <td>0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0</td>\n",
       "      <td>01/25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2761</td>\n",
       "      <td>5794</td>\n",
       "      <td>80</td>\n",
       "      <td>51</td>\n",
       "      <td>2630</td>\n",
       "      <td>461</td>\n",
       "      <td>0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0</td>\n",
       "      <td>01/26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>4535</td>\n",
       "      <td>6973</td>\n",
       "      <td>106</td>\n",
       "      <td>60</td>\n",
       "      <td>4369</td>\n",
       "      <td>976</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0</td>\n",
       "      <td>01/27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>5997</td>\n",
       "      <td>9239</td>\n",
       "      <td>132</td>\n",
       "      <td>103</td>\n",
       "      <td>5762</td>\n",
       "      <td>1239</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0</td>\n",
       "      <td>01/28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>7736</td>\n",
       "      <td>12167</td>\n",
       "      <td>170</td>\n",
       "      <td>124</td>\n",
       "      <td>7442</td>\n",
       "      <td>1370</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0</td>\n",
       "      <td>01/29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>9720</td>\n",
       "      <td>15238</td>\n",
       "      <td>213</td>\n",
       "      <td>171</td>\n",
       "      <td>9336</td>\n",
       "      <td>1527</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0</td>\n",
       "      <td>01/30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>11821</td>\n",
       "      <td>17988</td>\n",
       "      <td>259</td>\n",
       "      <td>243</td>\n",
       "      <td>11319</td>\n",
       "      <td>1795</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0</td>\n",
       "      <td>01/31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>14411</td>\n",
       "      <td>19544</td>\n",
       "      <td>304</td>\n",
       "      <td>328</td>\n",
       "      <td>13779</td>\n",
       "      <td>2110</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "      <td>02/01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>17238</td>\n",
       "      <td>21558</td>\n",
       "      <td>361</td>\n",
       "      <td>475</td>\n",
       "      <td>16402</td>\n",
       "      <td>2296</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.8</td>\n",
       "      <td>0</td>\n",
       "      <td>02/02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>20471</td>\n",
       "      <td>23214</td>\n",
       "      <td>425</td>\n",
       "      <td>632</td>\n",
       "      <td>19414</td>\n",
       "      <td>2788</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0</td>\n",
       "      <td>02/03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>24363</td>\n",
       "      <td>23260</td>\n",
       "      <td>491</td>\n",
       "      <td>892</td>\n",
       "      <td>22980</td>\n",
       "      <td>3219</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0</td>\n",
       "      <td>02/04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>28060</td>\n",
       "      <td>24702</td>\n",
       "      <td>564</td>\n",
       "      <td>1153</td>\n",
       "      <td>26343</td>\n",
       "      <td>3859</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>0</td>\n",
       "      <td>02/05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>31211</td>\n",
       "      <td>26359</td>\n",
       "      <td>637</td>\n",
       "      <td>1542</td>\n",
       "      <td>29032</td>\n",
       "      <td>4821</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>0</td>\n",
       "      <td>02/06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>34598</td>\n",
       "      <td>27657</td>\n",
       "      <td>723</td>\n",
       "      <td>2052</td>\n",
       "      <td>31823</td>\n",
       "      <td>6101</td>\n",
       "      <td>0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>5.9</td>\n",
       "      <td>0</td>\n",
       "      <td>02/07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>37251</td>\n",
       "      <td>28942</td>\n",
       "      <td>812</td>\n",
       "      <td>2651</td>\n",
       "      <td>33788</td>\n",
       "      <td>6188</td>\n",
       "      <td>0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>7.1</td>\n",
       "      <td>0</td>\n",
       "      <td>02/08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>40235</td>\n",
       "      <td>23589</td>\n",
       "      <td>909</td>\n",
       "      <td>3283</td>\n",
       "      <td>36043</td>\n",
       "      <td>6484</td>\n",
       "      <td>0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>8.2</td>\n",
       "      <td>0</td>\n",
       "      <td>02/09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>42708</td>\n",
       "      <td>21675</td>\n",
       "      <td>1017</td>\n",
       "      <td>3998</td>\n",
       "      <td>37693</td>\n",
       "      <td>7333</td>\n",
       "      <td>0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>9.4</td>\n",
       "      <td>0</td>\n",
       "      <td>02/10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>44730</td>\n",
       "      <td>16067</td>\n",
       "      <td>1114</td>\n",
       "      <td>4742</td>\n",
       "      <td>38874</td>\n",
       "      <td>8204</td>\n",
       "      <td>0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>10.6</td>\n",
       "      <td>0</td>\n",
       "      <td>02/11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>85366</td>\n",
       "      <td>6</td>\n",
       "      <td>4648</td>\n",
       "      <td>80192</td>\n",
       "      <td>526</td>\n",
       "      <td>6</td>\n",
       "      <td>1949</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.9</td>\n",
       "      <td>117</td>\n",
       "      <td>07/07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>85399</td>\n",
       "      <td>5</td>\n",
       "      <td>4648</td>\n",
       "      <td>80240</td>\n",
       "      <td>511</td>\n",
       "      <td>5</td>\n",
       "      <td>1958</td>\n",
       "      <td>5.4</td>\n",
       "      <td>94.0</td>\n",
       "      <td>112</td>\n",
       "      <td>07/08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>85445</td>\n",
       "      <td>8</td>\n",
       "      <td>4648</td>\n",
       "      <td>80268</td>\n",
       "      <td>529</td>\n",
       "      <td>4</td>\n",
       "      <td>1962</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.9</td>\n",
       "      <td>113</td>\n",
       "      <td>07/09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>85487</td>\n",
       "      <td>8</td>\n",
       "      <td>4648</td>\n",
       "      <td>80293</td>\n",
       "      <td>546</td>\n",
       "      <td>3</td>\n",
       "      <td>1964</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.9</td>\n",
       "      <td>111</td>\n",
       "      <td>07/10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>85522</td>\n",
       "      <td>7</td>\n",
       "      <td>4648</td>\n",
       "      <td>80314</td>\n",
       "      <td>560</td>\n",
       "      <td>3</td>\n",
       "      <td>1971</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.9</td>\n",
       "      <td>112</td>\n",
       "      <td>07/11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>85568</td>\n",
       "      <td>7</td>\n",
       "      <td>4648</td>\n",
       "      <td>80345</td>\n",
       "      <td>575</td>\n",
       "      <td>3</td>\n",
       "      <td>1979</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.9</td>\n",
       "      <td>110</td>\n",
       "      <td>07/12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>85623</td>\n",
       "      <td>5</td>\n",
       "      <td>4649</td>\n",
       "      <td>80376</td>\n",
       "      <td>598</td>\n",
       "      <td>3</td>\n",
       "      <td>1982</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.9</td>\n",
       "      <td>110</td>\n",
       "      <td>07/13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>85677</td>\n",
       "      <td>3</td>\n",
       "      <td>4649</td>\n",
       "      <td>80407</td>\n",
       "      <td>621</td>\n",
       "      <td>3</td>\n",
       "      <td>1988</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.8</td>\n",
       "      <td>110</td>\n",
       "      <td>07/14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>85697</td>\n",
       "      <td>3</td>\n",
       "      <td>4651</td>\n",
       "      <td>80445</td>\n",
       "      <td>601</td>\n",
       "      <td>3</td>\n",
       "      <td>1989</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.9</td>\n",
       "      <td>104</td>\n",
       "      <td>07/15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>85775</td>\n",
       "      <td>3</td>\n",
       "      <td>4651</td>\n",
       "      <td>80476</td>\n",
       "      <td>648</td>\n",
       "      <td>3</td>\n",
       "      <td>1998</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.8</td>\n",
       "      <td>104</td>\n",
       "      <td>07/16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>85857</td>\n",
       "      <td>4</td>\n",
       "      <td>4652</td>\n",
       "      <td>80508</td>\n",
       "      <td>697</td>\n",
       "      <td>3</td>\n",
       "      <td>2004</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.8</td>\n",
       "      <td>109</td>\n",
       "      <td>07/17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>85937</td>\n",
       "      <td>4</td>\n",
       "      <td>4653</td>\n",
       "      <td>80535</td>\n",
       "      <td>749</td>\n",
       "      <td>3</td>\n",
       "      <td>2007</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.7</td>\n",
       "      <td>147</td>\n",
       "      <td>07/18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>86068</td>\n",
       "      <td>4</td>\n",
       "      <td>4653</td>\n",
       "      <td>80579</td>\n",
       "      <td>836</td>\n",
       "      <td>5</td>\n",
       "      <td>2012</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.6</td>\n",
       "      <td>154</td>\n",
       "      <td>07/19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>86152</td>\n",
       "      <td>1</td>\n",
       "      <td>4653</td>\n",
       "      <td>80605</td>\n",
       "      <td>894</td>\n",
       "      <td>7</td>\n",
       "      <td>2015</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.6</td>\n",
       "      <td>149</td>\n",
       "      <td>07/20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>86226</td>\n",
       "      <td>1</td>\n",
       "      <td>4655</td>\n",
       "      <td>80650</td>\n",
       "      <td>921</td>\n",
       "      <td>6</td>\n",
       "      <td>2020</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.5</td>\n",
       "      <td>164</td>\n",
       "      <td>07/21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>86361</td>\n",
       "      <td>4</td>\n",
       "      <td>4655</td>\n",
       "      <td>80685</td>\n",
       "      <td>1021</td>\n",
       "      <td>11</td>\n",
       "      <td>2023</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.4</td>\n",
       "      <td>176</td>\n",
       "      <td>07/22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>86500</td>\n",
       "      <td>2</td>\n",
       "      <td>4656</td>\n",
       "      <td>80738</td>\n",
       "      <td>1106</td>\n",
       "      <td>12</td>\n",
       "      <td>2029</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.3</td>\n",
       "      <td>204</td>\n",
       "      <td>07/23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>86660</td>\n",
       "      <td>2</td>\n",
       "      <td>4657</td>\n",
       "      <td>80782</td>\n",
       "      <td>1221</td>\n",
       "      <td>11</td>\n",
       "      <td>2034</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.2</td>\n",
       "      <td>251</td>\n",
       "      <td>07/24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>86839</td>\n",
       "      <td>3</td>\n",
       "      <td>4659</td>\n",
       "      <td>80849</td>\n",
       "      <td>1331</td>\n",
       "      <td>18</td>\n",
       "      <td>2045</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.1</td>\n",
       "      <td>292</td>\n",
       "      <td>07/25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>87028</td>\n",
       "      <td>3</td>\n",
       "      <td>4659</td>\n",
       "      <td>80899</td>\n",
       "      <td>1470</td>\n",
       "      <td>21</td>\n",
       "      <td>2049</td>\n",
       "      <td>5.4</td>\n",
       "      <td>93.0</td>\n",
       "      <td>302</td>\n",
       "      <td>07/26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>87245</td>\n",
       "      <td>1</td>\n",
       "      <td>4663</td>\n",
       "      <td>80906</td>\n",
       "      <td>1676</td>\n",
       "      <td>20</td>\n",
       "      <td>2053</td>\n",
       "      <td>5.3</td>\n",
       "      <td>92.7</td>\n",
       "      <td>306</td>\n",
       "      <td>07/27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>87457</td>\n",
       "      <td>1</td>\n",
       "      <td>4664</td>\n",
       "      <td>80957</td>\n",
       "      <td>1836</td>\n",
       "      <td>25</td>\n",
       "      <td>2056</td>\n",
       "      <td>5.3</td>\n",
       "      <td>92.6</td>\n",
       "      <td>273</td>\n",
       "      <td>07/28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>87680</td>\n",
       "      <td>2</td>\n",
       "      <td>4665</td>\n",
       "      <td>81034</td>\n",
       "      <td>1981</td>\n",
       "      <td>33</td>\n",
       "      <td>2059</td>\n",
       "      <td>5.3</td>\n",
       "      <td>92.4</td>\n",
       "      <td>280</td>\n",
       "      <td>07/29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>87956</td>\n",
       "      <td>2</td>\n",
       "      <td>4666</td>\n",
       "      <td>81120</td>\n",
       "      <td>2170</td>\n",
       "      <td>41</td>\n",
       "      <td>2063</td>\n",
       "      <td>5.3</td>\n",
       "      <td>92.2</td>\n",
       "      <td>246</td>\n",
       "      <td>07/30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>88122</td>\n",
       "      <td>2</td>\n",
       "      <td>4668</td>\n",
       "      <td>81227</td>\n",
       "      <td>2227</td>\n",
       "      <td>39</td>\n",
       "      <td>2069</td>\n",
       "      <td>5.3</td>\n",
       "      <td>92.2</td>\n",
       "      <td>252</td>\n",
       "      <td>07/31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>88301</td>\n",
       "      <td>2</td>\n",
       "      <td>4672</td>\n",
       "      <td>81348</td>\n",
       "      <td>2281</td>\n",
       "      <td>36</td>\n",
       "      <td>2085</td>\n",
       "      <td>5.3</td>\n",
       "      <td>92.1</td>\n",
       "      <td>257</td>\n",
       "      <td>08/01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>88459</td>\n",
       "      <td>4</td>\n",
       "      <td>4676</td>\n",
       "      <td>81459</td>\n",
       "      <td>2324</td>\n",
       "      <td>35</td>\n",
       "      <td>2092</td>\n",
       "      <td>5.3</td>\n",
       "      <td>92.1</td>\n",
       "      <td>257</td>\n",
       "      <td>08/02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>88573</td>\n",
       "      <td>5</td>\n",
       "      <td>4679</td>\n",
       "      <td>81554</td>\n",
       "      <td>2340</td>\n",
       "      <td>36</td>\n",
       "      <td>2098</td>\n",
       "      <td>5.3</td>\n",
       "      <td>92.1</td>\n",
       "      <td>264</td>\n",
       "      <td>08/03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>88682</td>\n",
       "      <td>3</td>\n",
       "      <td>4683</td>\n",
       "      <td>81675</td>\n",
       "      <td>2324</td>\n",
       "      <td>36</td>\n",
       "      <td>2103</td>\n",
       "      <td>5.3</td>\n",
       "      <td>92.1</td>\n",
       "      <td>272</td>\n",
       "      <td>08/04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>88804</td>\n",
       "      <td>2</td>\n",
       "      <td>4684</td>\n",
       "      <td>81858</td>\n",
       "      <td>2262</td>\n",
       "      <td>34</td>\n",
       "      <td>2110</td>\n",
       "      <td>5.3</td>\n",
       "      <td>92.2</td>\n",
       "      <td>282</td>\n",
       "      <td>08/05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>206 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      累积确诊  疑似病例  累计死亡   累计治愈  现有确诊  重症  输入病例  死亡率   治愈率  无症状感染     日期\n",
       "0       41     0     1      0     0   0     0  2.4   0.0      0  01/13\n",
       "1       41     0     1      0     0   0     0  2.4   0.0      0  01/14\n",
       "2       41     0     2      5     0   0     0  4.9  12.2      0  01/15\n",
       "3       45     0     2      8     0   0     0  4.4  17.8      0  01/16\n",
       "4       62     0     2     12     0   0     0  3.2  19.4      0  01/17\n",
       "..     ...   ...   ...    ...   ...  ..   ...  ...   ...    ...    ...\n",
       "201  88301     2  4672  81348  2281  36  2085  5.3  92.1    257  08/01\n",
       "202  88459     4  4676  81459  2324  35  2092  5.3  92.1    257  08/02\n",
       "203  88573     5  4679  81554  2340  36  2098  5.3  92.1    264  08/03\n",
       "204  88682     3  4683  81675  2324  36  2103  5.3  92.1    272  08/04\n",
       "205  88804     2  4684  81858  2262  34  2110  5.3  92.2    282  08/05\n",
       "\n",
       "[206 rows x 11 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##读取国内每日疫情数据数据\n",
    "china_daily_data=pd.read_csv('./china_daily_data.csv',encoding='gbk')\n",
    "china_daily_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 206 entries, 0 to 205\n",
      "Data columns (total 11 columns):\n",
      "累积确诊     206 non-null int64\n",
      "疑似病例     206 non-null int64\n",
      "累计死亡     206 non-null int64\n",
      "累计治愈     206 non-null int64\n",
      "现有确诊     206 non-null int64\n",
      "重症       206 non-null int64\n",
      "输入病例     206 non-null int64\n",
      "死亡率      206 non-null float64\n",
      "治愈率      206 non-null float64\n",
      "无症状感染    206 non-null int64\n",
      "日期       206 non-null object\n",
      "dtypes: float64(2), int64(8), object(1)\n",
      "memory usage: 17.8+ KB\n"
     ]
    }
   ],
   "source": [
    "###查看各字段的数据类型\n",
    "china_daily_data.info()\n",
    "###从反馈信息来看，china_daily_data.csv总共存储了205条数据，其中float64(2), int64(8), object(1)，分别是'日期'数据类型为object，'死亡率'和'治愈率'数据类型为float，其他数据类型均为int\n",
    "###可以看出爬取的数据并无缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>累积确诊</th>\n",
       "      <th>疑似病例</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>重症</th>\n",
       "      <th>输入病例</th>\n",
       "      <th>死亡率</th>\n",
       "      <th>治愈率</th>\n",
       "      <th>无症状感染</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>206.000000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>206.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>72941.684466</td>\n",
       "      <td>2112.174757</td>\n",
       "      <td>3480.111650</td>\n",
       "      <td>60917.213592</td>\n",
       "      <td>8536.655340</td>\n",
       "      <td>1677.441748</td>\n",
       "      <td>1115.737864</td>\n",
       "      <td>4.462621</td>\n",
       "      <td>73.128155</td>\n",
       "      <td>299.961165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>25812.610393</td>\n",
       "      <td>5748.117629</td>\n",
       "      <td>1558.834302</td>\n",
       "      <td>30237.750623</td>\n",
       "      <td>15479.929609</td>\n",
       "      <td>3143.367884</td>\n",
       "      <td>838.591897</td>\n",
       "      <td>1.214631</td>\n",
       "      <td>34.057485</td>\n",
       "      <td>382.976530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>80601.250000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3022.500000</td>\n",
       "      <td>52530.000000</td>\n",
       "      <td>387.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>3.800000</td>\n",
       "      <td>65.175000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>84331.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>4642.000000</td>\n",
       "      <td>78531.000000</td>\n",
       "      <td>1283.000000</td>\n",
       "      <td>35.500000</td>\n",
       "      <td>1631.500000</td>\n",
       "      <td>5.300000</td>\n",
       "      <td>93.100000</td>\n",
       "      <td>110.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>84811.750000</td>\n",
       "      <td>183.750000</td>\n",
       "      <td>4645.000000</td>\n",
       "      <td>79919.750000</td>\n",
       "      <td>5972.000000</td>\n",
       "      <td>1705.000000</td>\n",
       "      <td>1843.000000</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>93.900000</td>\n",
       "      <td>401.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>88804.000000</td>\n",
       "      <td>28942.000000</td>\n",
       "      <td>4684.000000</td>\n",
       "      <td>81858.000000</td>\n",
       "      <td>58097.000000</td>\n",
       "      <td>11977.000000</td>\n",
       "      <td>2110.000000</td>\n",
       "      <td>5.500000</td>\n",
       "      <td>94.400000</td>\n",
       "      <td>1367.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               累积确诊          疑似病例         累计死亡          累计治愈          现有确诊  \\\n",
       "count    206.000000    206.000000   206.000000    206.000000    206.000000   \n",
       "mean   72941.684466   2112.174757  3480.111650  60917.213592   8536.655340   \n",
       "std    25812.610393   5748.117629  1558.834302  30237.750623  15479.929609   \n",
       "min       41.000000      0.000000     1.000000      0.000000      0.000000   \n",
       "25%    80601.250000      4.000000  3022.500000  52530.000000    387.000000   \n",
       "50%    84331.000000     11.000000  4642.000000  78531.000000   1283.000000   \n",
       "75%    84811.750000    183.750000  4645.000000  79919.750000   5972.000000   \n",
       "max    88804.000000  28942.000000  4684.000000  81858.000000  58097.000000   \n",
       "\n",
       "                 重症         输入病例         死亡率         治愈率        无症状感染  \n",
       "count    206.000000   206.000000  206.000000  206.000000   206.000000  \n",
       "mean    1677.441748  1115.737864    4.462621   73.128155   299.961165  \n",
       "std     3143.367884   838.591897    1.214631   34.057485   382.976530  \n",
       "min        0.000000     0.000000    1.500000    0.000000     0.000000  \n",
       "25%        7.000000    24.000000    3.800000   65.175000     0.000000  \n",
       "50%       35.500000  1631.500000    5.300000   93.100000   110.000000  \n",
       "75%     1705.000000  1843.000000    5.500000   93.900000   401.500000  \n",
       "max    11977.000000  2110.000000    5.500000   94.400000  1367.000000  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "####查看数据摘要信息\n",
    "china_daily_data.describe()\n",
    "###从反馈信息可以看到，截止到2020/8/4，总共累计确诊有88682人，死亡4683人，治愈816575人；\n",
    "###从1月13日到8月4日期间，现有确诊人数最高时达到58097人，重症人数最多时也高达11977人，无症状感染最多时也有1367人"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##2.国内各省份和地级市疫情数据分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###2.1国内各省疫情总数据分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>死亡率</th>\n",
       "      <th>治愈率</th>\n",
       "      <th>省份</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1347</td>\n",
       "      <td>3849</td>\n",
       "      <td>44</td>\n",
       "      <td>2458</td>\n",
       "      <td>1.14</td>\n",
       "      <td>63.86</td>\n",
       "      <td>香港</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>637</td>\n",
       "      <td>773</td>\n",
       "      <td>3</td>\n",
       "      <td>133</td>\n",
       "      <td>0.39</td>\n",
       "      <td>17.21</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>95</td>\n",
       "      <td>258</td>\n",
       "      <td>2</td>\n",
       "      <td>161</td>\n",
       "      <td>0.78</td>\n",
       "      <td>62.40</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>29</td>\n",
       "      <td>477</td>\n",
       "      <td>7</td>\n",
       "      <td>441</td>\n",
       "      <td>1.47</td>\n",
       "      <td>92.45</td>\n",
       "      <td>台湾</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22</td>\n",
       "      <td>757</td>\n",
       "      <td>7</td>\n",
       "      <td>728</td>\n",
       "      <td>0.92</td>\n",
       "      <td>96.17</td>\n",
       "      <td>上海</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>18</td>\n",
       "      <td>1687</td>\n",
       "      <td>8</td>\n",
       "      <td>1661</td>\n",
       "      <td>0.47</td>\n",
       "      <td>98.46</td>\n",
       "      <td>广东</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>12</td>\n",
       "      <td>805</td>\n",
       "      <td>7</td>\n",
       "      <td>786</td>\n",
       "      <td>0.87</td>\n",
       "      <td>97.64</td>\n",
       "      <td>山东</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>258</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>0.39</td>\n",
       "      <td>95.74</td>\n",
       "      <td>内蒙古</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>610</td>\n",
       "      <td>3</td>\n",
       "      <td>598</td>\n",
       "      <td>0.49</td>\n",
       "      <td>98.03</td>\n",
       "      <td>四川</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7</td>\n",
       "      <td>328</td>\n",
       "      <td>3</td>\n",
       "      <td>318</td>\n",
       "      <td>0.91</td>\n",
       "      <td>96.95</td>\n",
       "      <td>陕西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6</td>\n",
       "      <td>934</td>\n",
       "      <td>9</td>\n",
       "      <td>919</td>\n",
       "      <td>0.96</td>\n",
       "      <td>98.39</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5</td>\n",
       "      <td>205</td>\n",
       "      <td>3</td>\n",
       "      <td>197</td>\n",
       "      <td>1.46</td>\n",
       "      <td>96.10</td>\n",
       "      <td>天津</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>4</td>\n",
       "      <td>658</td>\n",
       "      <td>0</td>\n",
       "      <td>654</td>\n",
       "      <td>0.00</td>\n",
       "      <td>99.39</td>\n",
       "      <td>江苏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3</td>\n",
       "      <td>68138</td>\n",
       "      <td>4512</td>\n",
       "      <td>63623</td>\n",
       "      <td>6.62</td>\n",
       "      <td>93.37</td>\n",
       "      <td>湖北</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3</td>\n",
       "      <td>367</td>\n",
       "      <td>1</td>\n",
       "      <td>363</td>\n",
       "      <td>0.27</td>\n",
       "      <td>98.91</td>\n",
       "      <td>福建</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>191</td>\n",
       "      <td>2</td>\n",
       "      <td>187</td>\n",
       "      <td>1.05</td>\n",
       "      <td>97.91</td>\n",
       "      <td>云南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>1270</td>\n",
       "      <td>1</td>\n",
       "      <td>1268</td>\n",
       "      <td>0.08</td>\n",
       "      <td>99.84</td>\n",
       "      <td>浙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1</td>\n",
       "      <td>157</td>\n",
       "      <td>2</td>\n",
       "      <td>154</td>\n",
       "      <td>1.27</td>\n",
       "      <td>98.09</td>\n",
       "      <td>吉林</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>167</td>\n",
       "      <td>2</td>\n",
       "      <td>165</td>\n",
       "      <td>1.20</td>\n",
       "      <td>98.80</td>\n",
       "      <td>甘肃</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>1019</td>\n",
       "      <td>4</td>\n",
       "      <td>1015</td>\n",
       "      <td>0.39</td>\n",
       "      <td>99.61</td>\n",
       "      <td>湖南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>青海</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>2</td>\n",
       "      <td>253</td>\n",
       "      <td>0.78</td>\n",
       "      <td>99.22</td>\n",
       "      <td>广西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0</td>\n",
       "      <td>349</td>\n",
       "      <td>6</td>\n",
       "      <td>343</td>\n",
       "      <td>1.72</td>\n",
       "      <td>98.28</td>\n",
       "      <td>河北</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0</td>\n",
       "      <td>1276</td>\n",
       "      <td>22</td>\n",
       "      <td>1254</td>\n",
       "      <td>1.72</td>\n",
       "      <td>98.28</td>\n",
       "      <td>河南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0</td>\n",
       "      <td>201</td>\n",
       "      <td>0</td>\n",
       "      <td>201</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>山西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>932</td>\n",
       "      <td>1</td>\n",
       "      <td>931</td>\n",
       "      <td>0.11</td>\n",
       "      <td>99.89</td>\n",
       "      <td>江西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0</td>\n",
       "      <td>147</td>\n",
       "      <td>2</td>\n",
       "      <td>145</td>\n",
       "      <td>1.36</td>\n",
       "      <td>98.64</td>\n",
       "      <td>贵州</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0</td>\n",
       "      <td>171</td>\n",
       "      <td>6</td>\n",
       "      <td>165</td>\n",
       "      <td>3.51</td>\n",
       "      <td>96.49</td>\n",
       "      <td>海南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>澳门</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>西藏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0</td>\n",
       "      <td>583</td>\n",
       "      <td>6</td>\n",
       "      <td>577</td>\n",
       "      <td>1.03</td>\n",
       "      <td>98.97</td>\n",
       "      <td>重庆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0</td>\n",
       "      <td>947</td>\n",
       "      <td>13</td>\n",
       "      <td>934</td>\n",
       "      <td>1.37</td>\n",
       "      <td>98.63</td>\n",
       "      <td>黑龙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0</td>\n",
       "      <td>75</td>\n",
       "      <td>0</td>\n",
       "      <td>75</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>宁夏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0</td>\n",
       "      <td>991</td>\n",
       "      <td>6</td>\n",
       "      <td>985</td>\n",
       "      <td>0.61</td>\n",
       "      <td>99.39</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    现有确诊   累计确诊  累计死亡   累计治愈   死亡率     治愈率   省份\n",
       "0   1347   3849    44   2458  1.14   63.86   香港\n",
       "1    637    773     3    133  0.39   17.21   新疆\n",
       "2     95    258     2    161  0.78   62.40   辽宁\n",
       "3     29    477     7    441  1.47   92.45   台湾\n",
       "4     22    757     7    728  0.92   96.17   上海\n",
       "5     18   1687     8   1661  0.47   98.46   广东\n",
       "6     12    805     7    786  0.87   97.64   山东\n",
       "7     10    258     1    247  0.39   95.74  内蒙古\n",
       "8      9    610     3    598  0.49   98.03   四川\n",
       "9      7    328     3    318  0.91   96.95   陕西\n",
       "10     6    934     9    919  0.96   98.39   北京\n",
       "11     5    205     3    197  1.46   96.10   天津\n",
       "12     4    658     0    654  0.00   99.39   江苏\n",
       "13     3  68138  4512  63623  6.62   93.37   湖北\n",
       "14     3    367     1    363  0.27   98.91   福建\n",
       "15     2    191     2    187  1.05   97.91   云南\n",
       "16     1   1270     1   1268  0.08   99.84   浙江\n",
       "17     1    157     2    154  1.27   98.09   吉林\n",
       "18     0    167     2    165  1.20   98.80   甘肃\n",
       "19     0   1019     4   1015  0.39   99.61   湖南\n",
       "20     0     18     0     18  0.00  100.00   青海\n",
       "21     0    255     2    253  0.78   99.22   广西\n",
       "22     0    349     6    343  1.72   98.28   河北\n",
       "23     0   1276    22   1254  1.72   98.28   河南\n",
       "24     0    201     0    201  0.00  100.00   山西\n",
       "25     0    932     1    931  0.11   99.89   江西\n",
       "26     0    147     2    145  1.36   98.64   贵州\n",
       "27     0    171     6    165  3.51   96.49   海南\n",
       "28     0     46     0     46  0.00  100.00   澳门\n",
       "29     0      1     0      1  0.00  100.00   西藏\n",
       "30     0    583     6    577  1.03   98.97   重庆\n",
       "31     0    947    13    934  1.37   98.63  黑龙江\n",
       "32     0     75     0     75  0.00  100.00   宁夏\n",
       "33     0    991     6    985  0.61   99.39   安徽"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "###读取国内各省疫情总数据\n",
    "china_province_data=pd.read_csv('./china_province_data.csv',encoding='gbk')\n",
    "china_province_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 34 entries, 0 to 33\n",
      "Data columns (total 7 columns):\n",
      "现有确诊    34 non-null int64\n",
      "累计确诊    34 non-null int64\n",
      "累计死亡    34 non-null int64\n",
      "累计治愈    34 non-null int64\n",
      "死亡率     34 non-null float64\n",
      "治愈率     34 non-null float64\n",
      "省份      34 non-null object\n",
      "dtypes: float64(2), int64(4), object(1)\n",
      "memory usage: 2.0+ KB\n"
     ]
    }
   ],
   "source": [
    "###查看各字段的数据类型\n",
    "china_province_data.info()\n",
    "##china_province_data.csv总共含有34条数据，float64(2), int64(4), object(1)，其中'省份'数据类型为object，'死亡率'和'治愈率'数据类型为float，其他数据类型均为int\n",
    "##并无数据缺失"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>死亡率</th>\n",
       "      <th>治愈率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>34.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>34.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>65.029412</td>\n",
       "      <td>2614.705882</td>\n",
       "      <td>137.794118</td>\n",
       "      <td>2411.882353</td>\n",
       "      <td>0.980588</td>\n",
       "      <td>93.738529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>251.513417</td>\n",
       "      <td>11599.220769</td>\n",
       "      <td>772.945636</td>\n",
       "      <td>10829.069181</td>\n",
       "      <td>1.229116</td>\n",
       "      <td>16.000902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>17.210000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>193.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>165.000000</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>96.605000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>422.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>353.000000</td>\n",
       "      <td>0.825000</td>\n",
       "      <td>98.425000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.500000</td>\n",
       "      <td>933.500000</td>\n",
       "      <td>6.750000</td>\n",
       "      <td>928.000000</td>\n",
       "      <td>1.252500</td>\n",
       "      <td>99.390000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1347.000000</td>\n",
       "      <td>68138.000000</td>\n",
       "      <td>4512.000000</td>\n",
       "      <td>63623.000000</td>\n",
       "      <td>6.620000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              现有确诊          累计确诊         累计死亡          累计治愈        死亡率  \\\n",
       "count    34.000000     34.000000    34.000000     34.000000  34.000000   \n",
       "mean     65.029412   2614.705882   137.794118   2411.882353   0.980588   \n",
       "std     251.513417  11599.220769   772.945636  10829.069181   1.229116   \n",
       "min       0.000000      1.000000     0.000000      1.000000   0.000000   \n",
       "25%       0.000000    193.500000     1.000000    165.000000   0.300000   \n",
       "50%       1.000000    422.000000     3.000000    353.000000   0.825000   \n",
       "75%       8.500000    933.500000     6.750000    928.000000   1.252500   \n",
       "max    1347.000000  68138.000000  4512.000000  63623.000000   6.620000   \n",
       "\n",
       "              治愈率  \n",
       "count   34.000000  \n",
       "mean    93.738529  \n",
       "std     16.000902  \n",
       "min     17.210000  \n",
       "25%     96.605000  \n",
       "50%     98.425000  \n",
       "75%     99.390000  \n",
       "max    100.000000  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "####查看数据摘要信息\n",
    "china_province_data.describe()\n",
    "###死亡人数最高的省份死亡人数有4512人，死亡率最高的省份死亡率为6.62%，治愈率最高的省份治愈率为100%\n",
    "###累计确诊人数平均约为2611人，死亡人数平均约为138人，治愈人数平均约为2407人，死亡率平均为0.98%，治愈率平均约为93.7%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>死亡率</th>\n",
       "      <th>治愈率</th>\n",
       "      <th>省份</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3</td>\n",
       "      <td>68138</td>\n",
       "      <td>4512</td>\n",
       "      <td>63623</td>\n",
       "      <td>6.62</td>\n",
       "      <td>93.37</td>\n",
       "      <td>湖北</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1347</td>\n",
       "      <td>3849</td>\n",
       "      <td>44</td>\n",
       "      <td>2458</td>\n",
       "      <td>1.14</td>\n",
       "      <td>63.86</td>\n",
       "      <td>香港</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>18</td>\n",
       "      <td>1687</td>\n",
       "      <td>8</td>\n",
       "      <td>1661</td>\n",
       "      <td>0.47</td>\n",
       "      <td>98.46</td>\n",
       "      <td>广东</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0</td>\n",
       "      <td>1276</td>\n",
       "      <td>22</td>\n",
       "      <td>1254</td>\n",
       "      <td>1.72</td>\n",
       "      <td>98.28</td>\n",
       "      <td>河南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>1270</td>\n",
       "      <td>1</td>\n",
       "      <td>1268</td>\n",
       "      <td>0.08</td>\n",
       "      <td>99.84</td>\n",
       "      <td>浙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>1019</td>\n",
       "      <td>4</td>\n",
       "      <td>1015</td>\n",
       "      <td>0.39</td>\n",
       "      <td>99.61</td>\n",
       "      <td>湖南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0</td>\n",
       "      <td>991</td>\n",
       "      <td>6</td>\n",
       "      <td>985</td>\n",
       "      <td>0.61</td>\n",
       "      <td>99.39</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0</td>\n",
       "      <td>947</td>\n",
       "      <td>13</td>\n",
       "      <td>934</td>\n",
       "      <td>1.37</td>\n",
       "      <td>98.63</td>\n",
       "      <td>黑龙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6</td>\n",
       "      <td>934</td>\n",
       "      <td>9</td>\n",
       "      <td>919</td>\n",
       "      <td>0.96</td>\n",
       "      <td>98.39</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>932</td>\n",
       "      <td>1</td>\n",
       "      <td>931</td>\n",
       "      <td>0.11</td>\n",
       "      <td>99.89</td>\n",
       "      <td>江西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>12</td>\n",
       "      <td>805</td>\n",
       "      <td>7</td>\n",
       "      <td>786</td>\n",
       "      <td>0.87</td>\n",
       "      <td>97.64</td>\n",
       "      <td>山东</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>637</td>\n",
       "      <td>773</td>\n",
       "      <td>3</td>\n",
       "      <td>133</td>\n",
       "      <td>0.39</td>\n",
       "      <td>17.21</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22</td>\n",
       "      <td>757</td>\n",
       "      <td>7</td>\n",
       "      <td>728</td>\n",
       "      <td>0.92</td>\n",
       "      <td>96.17</td>\n",
       "      <td>上海</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>4</td>\n",
       "      <td>658</td>\n",
       "      <td>0</td>\n",
       "      <td>654</td>\n",
       "      <td>0.00</td>\n",
       "      <td>99.39</td>\n",
       "      <td>江苏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>610</td>\n",
       "      <td>3</td>\n",
       "      <td>598</td>\n",
       "      <td>0.49</td>\n",
       "      <td>98.03</td>\n",
       "      <td>四川</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0</td>\n",
       "      <td>583</td>\n",
       "      <td>6</td>\n",
       "      <td>577</td>\n",
       "      <td>1.03</td>\n",
       "      <td>98.97</td>\n",
       "      <td>重庆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>29</td>\n",
       "      <td>477</td>\n",
       "      <td>7</td>\n",
       "      <td>441</td>\n",
       "      <td>1.47</td>\n",
       "      <td>92.45</td>\n",
       "      <td>台湾</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3</td>\n",
       "      <td>367</td>\n",
       "      <td>1</td>\n",
       "      <td>363</td>\n",
       "      <td>0.27</td>\n",
       "      <td>98.91</td>\n",
       "      <td>福建</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0</td>\n",
       "      <td>349</td>\n",
       "      <td>6</td>\n",
       "      <td>343</td>\n",
       "      <td>1.72</td>\n",
       "      <td>98.28</td>\n",
       "      <td>河北</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7</td>\n",
       "      <td>328</td>\n",
       "      <td>3</td>\n",
       "      <td>318</td>\n",
       "      <td>0.91</td>\n",
       "      <td>96.95</td>\n",
       "      <td>陕西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>258</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>0.39</td>\n",
       "      <td>95.74</td>\n",
       "      <td>内蒙古</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>95</td>\n",
       "      <td>258</td>\n",
       "      <td>2</td>\n",
       "      <td>161</td>\n",
       "      <td>0.78</td>\n",
       "      <td>62.40</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>2</td>\n",
       "      <td>253</td>\n",
       "      <td>0.78</td>\n",
       "      <td>99.22</td>\n",
       "      <td>广西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5</td>\n",
       "      <td>205</td>\n",
       "      <td>3</td>\n",
       "      <td>197</td>\n",
       "      <td>1.46</td>\n",
       "      <td>96.10</td>\n",
       "      <td>天津</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0</td>\n",
       "      <td>201</td>\n",
       "      <td>0</td>\n",
       "      <td>201</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>山西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>191</td>\n",
       "      <td>2</td>\n",
       "      <td>187</td>\n",
       "      <td>1.05</td>\n",
       "      <td>97.91</td>\n",
       "      <td>云南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0</td>\n",
       "      <td>171</td>\n",
       "      <td>6</td>\n",
       "      <td>165</td>\n",
       "      <td>3.51</td>\n",
       "      <td>96.49</td>\n",
       "      <td>海南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>167</td>\n",
       "      <td>2</td>\n",
       "      <td>165</td>\n",
       "      <td>1.20</td>\n",
       "      <td>98.80</td>\n",
       "      <td>甘肃</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1</td>\n",
       "      <td>157</td>\n",
       "      <td>2</td>\n",
       "      <td>154</td>\n",
       "      <td>1.27</td>\n",
       "      <td>98.09</td>\n",
       "      <td>吉林</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0</td>\n",
       "      <td>147</td>\n",
       "      <td>2</td>\n",
       "      <td>145</td>\n",
       "      <td>1.36</td>\n",
       "      <td>98.64</td>\n",
       "      <td>贵州</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0</td>\n",
       "      <td>75</td>\n",
       "      <td>0</td>\n",
       "      <td>75</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>宁夏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>澳门</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>青海</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>西藏</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    现有确诊   累计确诊  累计死亡   累计治愈   死亡率     治愈率   省份\n",
       "13     3  68138  4512  63623  6.62   93.37   湖北\n",
       "0   1347   3849    44   2458  1.14   63.86   香港\n",
       "5     18   1687     8   1661  0.47   98.46   广东\n",
       "23     0   1276    22   1254  1.72   98.28   河南\n",
       "16     1   1270     1   1268  0.08   99.84   浙江\n",
       "19     0   1019     4   1015  0.39   99.61   湖南\n",
       "33     0    991     6    985  0.61   99.39   安徽\n",
       "31     0    947    13    934  1.37   98.63  黑龙江\n",
       "10     6    934     9    919  0.96   98.39   北京\n",
       "25     0    932     1    931  0.11   99.89   江西\n",
       "6     12    805     7    786  0.87   97.64   山东\n",
       "1    637    773     3    133  0.39   17.21   新疆\n",
       "4     22    757     7    728  0.92   96.17   上海\n",
       "12     4    658     0    654  0.00   99.39   江苏\n",
       "8      9    610     3    598  0.49   98.03   四川\n",
       "30     0    583     6    577  1.03   98.97   重庆\n",
       "3     29    477     7    441  1.47   92.45   台湾\n",
       "14     3    367     1    363  0.27   98.91   福建\n",
       "22     0    349     6    343  1.72   98.28   河北\n",
       "9      7    328     3    318  0.91   96.95   陕西\n",
       "7     10    258     1    247  0.39   95.74  内蒙古\n",
       "2     95    258     2    161  0.78   62.40   辽宁\n",
       "21     0    255     2    253  0.78   99.22   广西\n",
       "11     5    205     3    197  1.46   96.10   天津\n",
       "24     0    201     0    201  0.00  100.00   山西\n",
       "15     2    191     2    187  1.05   97.91   云南\n",
       "27     0    171     6    165  3.51   96.49   海南\n",
       "18     0    167     2    165  1.20   98.80   甘肃\n",
       "17     1    157     2    154  1.27   98.09   吉林\n",
       "26     0    147     2    145  1.36   98.64   贵州\n",
       "32     0     75     0     75  0.00  100.00   宁夏\n",
       "28     0     46     0     46  0.00  100.00   澳门\n",
       "20     0     18     0     18  0.00  100.00   青海\n",
       "29     0      1     0      1  0.00  100.00   西藏"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##按'累计确诊'降序排序\n",
    "china_province_data.reindex(china_province_data['累计确诊'].sort_values(ascending=False).index)\n",
    "###从排序后的数据可以看出，累计确诊人数最高的是湖北\n",
    "##还可以看到确诊人数在1000人以上的有6各城市，分别为湖北 68138人、香港 3849人、广东 1687人 、河南 1276人、浙江 1270人、湖南 1019人"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>死亡率</th>\n",
       "      <th>治愈率</th>\n",
       "      <th>省份</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>637</td>\n",
       "      <td>773</td>\n",
       "      <td>3</td>\n",
       "      <td>133</td>\n",
       "      <td>0.39</td>\n",
       "      <td>17.21</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>95</td>\n",
       "      <td>258</td>\n",
       "      <td>2</td>\n",
       "      <td>161</td>\n",
       "      <td>0.78</td>\n",
       "      <td>62.40</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1347</td>\n",
       "      <td>3849</td>\n",
       "      <td>44</td>\n",
       "      <td>2458</td>\n",
       "      <td>1.14</td>\n",
       "      <td>63.86</td>\n",
       "      <td>香港</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>29</td>\n",
       "      <td>477</td>\n",
       "      <td>7</td>\n",
       "      <td>441</td>\n",
       "      <td>1.47</td>\n",
       "      <td>92.45</td>\n",
       "      <td>台湾</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3</td>\n",
       "      <td>68138</td>\n",
       "      <td>4512</td>\n",
       "      <td>63623</td>\n",
       "      <td>6.62</td>\n",
       "      <td>93.37</td>\n",
       "      <td>湖北</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>258</td>\n",
       "      <td>1</td>\n",
       "      <td>247</td>\n",
       "      <td>0.39</td>\n",
       "      <td>95.74</td>\n",
       "      <td>内蒙古</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5</td>\n",
       "      <td>205</td>\n",
       "      <td>3</td>\n",
       "      <td>197</td>\n",
       "      <td>1.46</td>\n",
       "      <td>96.10</td>\n",
       "      <td>天津</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22</td>\n",
       "      <td>757</td>\n",
       "      <td>7</td>\n",
       "      <td>728</td>\n",
       "      <td>0.92</td>\n",
       "      <td>96.17</td>\n",
       "      <td>上海</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0</td>\n",
       "      <td>171</td>\n",
       "      <td>6</td>\n",
       "      <td>165</td>\n",
       "      <td>3.51</td>\n",
       "      <td>96.49</td>\n",
       "      <td>海南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7</td>\n",
       "      <td>328</td>\n",
       "      <td>3</td>\n",
       "      <td>318</td>\n",
       "      <td>0.91</td>\n",
       "      <td>96.95</td>\n",
       "      <td>陕西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>12</td>\n",
       "      <td>805</td>\n",
       "      <td>7</td>\n",
       "      <td>786</td>\n",
       "      <td>0.87</td>\n",
       "      <td>97.64</td>\n",
       "      <td>山东</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>191</td>\n",
       "      <td>2</td>\n",
       "      <td>187</td>\n",
       "      <td>1.05</td>\n",
       "      <td>97.91</td>\n",
       "      <td>云南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>610</td>\n",
       "      <td>3</td>\n",
       "      <td>598</td>\n",
       "      <td>0.49</td>\n",
       "      <td>98.03</td>\n",
       "      <td>四川</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1</td>\n",
       "      <td>157</td>\n",
       "      <td>2</td>\n",
       "      <td>154</td>\n",
       "      <td>1.27</td>\n",
       "      <td>98.09</td>\n",
       "      <td>吉林</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0</td>\n",
       "      <td>1276</td>\n",
       "      <td>22</td>\n",
       "      <td>1254</td>\n",
       "      <td>1.72</td>\n",
       "      <td>98.28</td>\n",
       "      <td>河南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0</td>\n",
       "      <td>349</td>\n",
       "      <td>6</td>\n",
       "      <td>343</td>\n",
       "      <td>1.72</td>\n",
       "      <td>98.28</td>\n",
       "      <td>河北</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6</td>\n",
       "      <td>934</td>\n",
       "      <td>9</td>\n",
       "      <td>919</td>\n",
       "      <td>0.96</td>\n",
       "      <td>98.39</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>18</td>\n",
       "      <td>1687</td>\n",
       "      <td>8</td>\n",
       "      <td>1661</td>\n",
       "      <td>0.47</td>\n",
       "      <td>98.46</td>\n",
       "      <td>广东</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0</td>\n",
       "      <td>947</td>\n",
       "      <td>13</td>\n",
       "      <td>934</td>\n",
       "      <td>1.37</td>\n",
       "      <td>98.63</td>\n",
       "      <td>黑龙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0</td>\n",
       "      <td>147</td>\n",
       "      <td>2</td>\n",
       "      <td>145</td>\n",
       "      <td>1.36</td>\n",
       "      <td>98.64</td>\n",
       "      <td>贵州</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>167</td>\n",
       "      <td>2</td>\n",
       "      <td>165</td>\n",
       "      <td>1.20</td>\n",
       "      <td>98.80</td>\n",
       "      <td>甘肃</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3</td>\n",
       "      <td>367</td>\n",
       "      <td>1</td>\n",
       "      <td>363</td>\n",
       "      <td>0.27</td>\n",
       "      <td>98.91</td>\n",
       "      <td>福建</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0</td>\n",
       "      <td>583</td>\n",
       "      <td>6</td>\n",
       "      <td>577</td>\n",
       "      <td>1.03</td>\n",
       "      <td>98.97</td>\n",
       "      <td>重庆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>255</td>\n",
       "      <td>2</td>\n",
       "      <td>253</td>\n",
       "      <td>0.78</td>\n",
       "      <td>99.22</td>\n",
       "      <td>广西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0</td>\n",
       "      <td>991</td>\n",
       "      <td>6</td>\n",
       "      <td>985</td>\n",
       "      <td>0.61</td>\n",
       "      <td>99.39</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>4</td>\n",
       "      <td>658</td>\n",
       "      <td>0</td>\n",
       "      <td>654</td>\n",
       "      <td>0.00</td>\n",
       "      <td>99.39</td>\n",
       "      <td>江苏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>1019</td>\n",
       "      <td>4</td>\n",
       "      <td>1015</td>\n",
       "      <td>0.39</td>\n",
       "      <td>99.61</td>\n",
       "      <td>湖南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>1270</td>\n",
       "      <td>1</td>\n",
       "      <td>1268</td>\n",
       "      <td>0.08</td>\n",
       "      <td>99.84</td>\n",
       "      <td>浙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>932</td>\n",
       "      <td>1</td>\n",
       "      <td>931</td>\n",
       "      <td>0.11</td>\n",
       "      <td>99.89</td>\n",
       "      <td>江西</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>青海</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>澳门</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>西藏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0</td>\n",
       "      <td>75</td>\n",
       "      <td>0</td>\n",
       "      <td>75</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>宁夏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0</td>\n",
       "      <td>201</td>\n",
       "      <td>0</td>\n",
       "      <td>201</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>山西</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    现有确诊   累计确诊  累计死亡   累计治愈   死亡率     治愈率   省份\n",
       "1    637    773     3    133  0.39   17.21   新疆\n",
       "2     95    258     2    161  0.78   62.40   辽宁\n",
       "0   1347   3849    44   2458  1.14   63.86   香港\n",
       "3     29    477     7    441  1.47   92.45   台湾\n",
       "13     3  68138  4512  63623  6.62   93.37   湖北\n",
       "7     10    258     1    247  0.39   95.74  内蒙古\n",
       "11     5    205     3    197  1.46   96.10   天津\n",
       "4     22    757     7    728  0.92   96.17   上海\n",
       "27     0    171     6    165  3.51   96.49   海南\n",
       "9      7    328     3    318  0.91   96.95   陕西\n",
       "6     12    805     7    786  0.87   97.64   山东\n",
       "15     2    191     2    187  1.05   97.91   云南\n",
       "8      9    610     3    598  0.49   98.03   四川\n",
       "17     1    157     2    154  1.27   98.09   吉林\n",
       "23     0   1276    22   1254  1.72   98.28   河南\n",
       "22     0    349     6    343  1.72   98.28   河北\n",
       "10     6    934     9    919  0.96   98.39   北京\n",
       "5     18   1687     8   1661  0.47   98.46   广东\n",
       "31     0    947    13    934  1.37   98.63  黑龙江\n",
       "26     0    147     2    145  1.36   98.64   贵州\n",
       "18     0    167     2    165  1.20   98.80   甘肃\n",
       "14     3    367     1    363  0.27   98.91   福建\n",
       "30     0    583     6    577  1.03   98.97   重庆\n",
       "21     0    255     2    253  0.78   99.22   广西\n",
       "33     0    991     6    985  0.61   99.39   安徽\n",
       "12     4    658     0    654  0.00   99.39   江苏\n",
       "19     0   1019     4   1015  0.39   99.61   湖南\n",
       "16     1   1270     1   1268  0.08   99.84   浙江\n",
       "25     0    932     1    931  0.11   99.89   江西\n",
       "20     0     18     0     18  0.00  100.00   青海\n",
       "28     0     46     0     46  0.00  100.00   澳门\n",
       "29     0      1     0      1  0.00  100.00   西藏\n",
       "32     0     75     0     75  0.00  100.00   宁夏\n",
       "24     0    201     0    201  0.00  100.00   山西"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##按'治愈率'升序排序\n",
    "china_province_data.reindex(china_province_data['治愈率'].sort_values(ascending=True).index)\n",
    "##治愈率最低的省份是新疆，只有16.76%，其次是辽宁，只有62.40%\n",
    "##治愈率在90%以下的省份只有3个，分别是新疆、辽宁、香港"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##2.2国内各省份每天疫情数据分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>新增确诊</th>\n",
       "      <th>新增治愈</th>\n",
       "      <th>新增死亡</th>\n",
       "      <th>日期</th>\n",
       "      <th>省份</th>\n",
       "      <th>国家</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>102</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>01/28</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>111</td>\n",
       "      <td>1</td>\n",
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       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>01/29</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>132</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>21.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>01/30</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>156</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>01/31</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>183</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>27.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>02/01</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>212</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>02/02</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>228</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>16.0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>02/03</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>253</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>02/04</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>274</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>02/05</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>297</td>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>02/06</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>315</td>\n",
       "      <td>2</td>\n",
       "      <td>34</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>02/07</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>326</td>\n",
       "      <td>2</td>\n",
       "      <td>37</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>02/08</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>337</td>\n",
       "      <td>2</td>\n",
       "      <td>44</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>02/09</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>342</td>\n",
       "      <td>3</td>\n",
       "      <td>48</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>02/10</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>352</td>\n",
       "      <td>3</td>\n",
       "      <td>56</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>02/11</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>366</td>\n",
       "      <td>3</td>\n",
       "      <td>68</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>02/12</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>366</td>\n",
       "      <td>3</td>\n",
       "      <td>68</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>02/13</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>372</td>\n",
       "      <td>3</td>\n",
       "      <td>79</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>02/14</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>380</td>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>02/15</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>381</td>\n",
       "      <td>4</td>\n",
       "      <td>114</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>02/16</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>387</td>\n",
       "      <td>4</td>\n",
       "      <td>122</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>02/17</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>393</td>\n",
       "      <td>4</td>\n",
       "      <td>145</td>\n",
       "      <td>6.0</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>02/18</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>395</td>\n",
       "      <td>4</td>\n",
       "      <td>153</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>02/19</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>396</td>\n",
       "      <td>4</td>\n",
       "      <td>169</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>02/20</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>399</td>\n",
       "      <td>4</td>\n",
       "      <td>178</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>02/21</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>399</td>\n",
       "      <td>4</td>\n",
       "      <td>189</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>02/22</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>399</td>\n",
       "      <td>4</td>\n",
       "      <td>198</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>02/23</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>400</td>\n",
       "      <td>4</td>\n",
       "      <td>215</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>02/24</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>400</td>\n",
       "      <td>4</td>\n",
       "      <td>235</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>02/25</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>410</td>\n",
       "      <td>5</td>\n",
       "      <td>248</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>02/26</td>\n",
       "      <td>北京</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6614</th>\n",
       "      <td>76</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/08</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6615</th>\n",
       "      <td>76</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/09</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6616</th>\n",
       "      <td>76</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/10</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6617</th>\n",
       "      <td>76</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/11</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6618</th>\n",
       "      <td>76</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/12</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6619</th>\n",
       "      <td>76</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/13</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6620</th>\n",
       "      <td>76</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/14</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6621</th>\n",
       "      <td>76</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/15</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6622</th>\n",
       "      <td>77</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/16</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6623</th>\n",
       "      <td>93</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/17</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6624</th>\n",
       "      <td>106</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/18</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6625</th>\n",
       "      <td>123</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/19</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6626</th>\n",
       "      <td>131</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/20</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6627</th>\n",
       "      <td>140</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/21</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6628</th>\n",
       "      <td>158</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/22</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6629</th>\n",
       "      <td>171</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/23</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6630</th>\n",
       "      <td>191</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/24</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6631</th>\n",
       "      <td>213</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/25</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6632</th>\n",
       "      <td>254</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/26</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6633</th>\n",
       "      <td>311</td>\n",
       "      <td>3</td>\n",
       "      <td>73</td>\n",
       "      <td>57.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>07/27</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6634</th>\n",
       "      <td>400</td>\n",
       "      <td>3</td>\n",
       "      <td>75</td>\n",
       "      <td>89.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>07/28</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6635</th>\n",
       "      <td>496</td>\n",
       "      <td>3</td>\n",
       "      <td>79</td>\n",
       "      <td>96.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>07/29</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6636</th>\n",
       "      <td>608</td>\n",
       "      <td>3</td>\n",
       "      <td>82</td>\n",
       "      <td>112.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>07/30</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6637</th>\n",
       "      <td>639</td>\n",
       "      <td>3</td>\n",
       "      <td>89</td>\n",
       "      <td>31.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>07/31</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6638</th>\n",
       "      <td>668</td>\n",
       "      <td>3</td>\n",
       "      <td>96</td>\n",
       "      <td>30.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>08/01</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6639</th>\n",
       "      <td>696</td>\n",
       "      <td>3</td>\n",
       "      <td>103</td>\n",
       "      <td>28.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>08/02</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6640</th>\n",
       "      <td>724</td>\n",
       "      <td>3</td>\n",
       "      <td>115</td>\n",
       "      <td>28.0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>08/03</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6641</th>\n",
       "      <td>746</td>\n",
       "      <td>3</td>\n",
       "      <td>125</td>\n",
       "      <td>22.0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>08/04</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6642</th>\n",
       "      <td>773</td>\n",
       "      <td>3</td>\n",
       "      <td>133</td>\n",
       "      <td>27.0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>08/05</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6643</th>\n",
       "      <td>773</td>\n",
       "      <td>3</td>\n",
       "      <td>133</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>08/06</td>\n",
       "      <td>新疆</td>\n",
       "      <td>中国</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6644 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      累计确诊  累计死亡  累计治愈  新增确诊  新增治愈  新增死亡     日期  省份  国家\n",
       "0      102     1     4  11.0     0     0  01/28  北京  中国\n",
       "1      111     1     4   9.0     0     0  01/29  北京  中国\n",
       "2      132     1     5  21.0     1     0  01/30  北京  中国\n",
       "3      156     1     5  24.0     0     0  01/31  北京  中国\n",
       "4      183     1     9  27.0     4     0  02/01  北京  中国\n",
       "...    ...   ...   ...   ...   ...   ...    ...  ..  ..\n",
       "6639   696     3   103  28.0     7     0  08/02  新疆  中国\n",
       "6640   724     3   115  28.0    12     0  08/03  新疆  中国\n",
       "6641   746     3   125  22.0    10     0  08/04  新疆  中国\n",
       "6642   773     3   133  27.0     8     0  08/05  新疆  中国\n",
       "6643   773     3   133  27.0     0     0  08/06  新疆  中国\n",
       "\n",
       "[6644 rows x 9 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##读取数据\n",
    "china_province_daily_data=pd.read_csv('./china_province_daily_data.csv',encoding='gbk')\n",
    "china_province_daily_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6644 entries, 0 to 6643\n",
      "Data columns (total 9 columns):\n",
      "累计确诊    6644 non-null int64\n",
      "累计死亡    6644 non-null int64\n",
      "累计治愈    6644 non-null int64\n",
      "新增确诊    6643 non-null float64\n",
      "新增治愈    6644 non-null int64\n",
      "新增死亡    6644 non-null int64\n",
      "日期      6644 non-null object\n",
      "省份      6644 non-null object\n",
      "国家      6644 non-null object\n",
      "dtypes: float64(1), int64(5), object(3)\n",
      "memory usage: 467.3+ KB\n"
     ]
    }
   ],
   "source": [
    "###查看各字段的数据类型\n",
    "china_province_daily_data.info()\n",
    "##china_province_daily_data.csv总共有6611条数据，dtypes: float64(1), int64(5), object(3)，其中'日期','省份','国家'为object，'新增确诊'为float，其余为int\n",
    "##没有数据缺失"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>新增确诊</th>\n",
       "      <th>新增治愈</th>\n",
       "      <th>新增死亡</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6644.000000</td>\n",
       "      <td>6644.000000</td>\n",
       "      <td>6644.000000</td>\n",
       "      <td>6643.000000</td>\n",
       "      <td>6644.000000</td>\n",
       "      <td>6644.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2274.201084</td>\n",
       "      <td>108.788682</td>\n",
       "      <td>1900.946117</td>\n",
       "      <td>13.398013</td>\n",
       "      <td>12.459964</td>\n",
       "      <td>0.509633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>10821.696403</td>\n",
       "      <td>644.750640</td>\n",
       "      <td>9443.672168</td>\n",
       "      <td>225.407928</td>\n",
       "      <td>123.206240</td>\n",
       "      <td>6.650343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-15.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>138.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>296.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>234.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>788.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>654.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>68138.000000</td>\n",
       "      <td>4512.000000</td>\n",
       "      <td>64435.000000</td>\n",
       "      <td>14840.000000</td>\n",
       "      <td>3203.000000</td>\n",
       "      <td>242.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               累计确诊         累计死亡          累计治愈          新增确诊         新增治愈  \\\n",
       "count   6644.000000  6644.000000   6644.000000   6643.000000  6644.000000   \n",
       "mean    2274.201084   108.788682   1900.946117     13.398013    12.459964   \n",
       "std    10821.696403   644.750640   9443.672168    225.407928   123.206240   \n",
       "min        0.000000     0.000000      0.000000     -1.000000   -15.000000   \n",
       "25%      138.000000     1.000000     75.000000      0.000000     0.000000   \n",
       "50%      296.000000     2.000000    234.000000      0.000000     0.000000   \n",
       "75%      788.000000     6.000000    654.000000      1.000000     1.000000   \n",
       "max    68138.000000  4512.000000  64435.000000  14840.000000  3203.000000   \n",
       "\n",
       "              新增死亡  \n",
       "count  6644.000000  \n",
       "mean      0.509633  \n",
       "std       6.650343  \n",
       "min      -1.000000  \n",
       "25%       0.000000  \n",
       "50%       0.000000  \n",
       "75%       0.000000  \n",
       "max     242.000000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "####查看数据摘要信息\n",
    "china_province_daily_data.describe()\n",
    "###从数据的数据摘要信息可以看出，国内平均每天新增确诊人数约为13人，新增治愈人数约为12人，新增死亡人数约为7人\n",
    "###国内各省每天新增确诊最高为14840人，新增死亡人数最高为242人"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##2.3中国各地市级疫情总数据分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>疑似病例</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>死亡率</th>\n",
       "      <th>治愈率</th>\n",
       "      <th>城市</th>\n",
       "      <th>省份</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1347</td>\n",
       "      <td>3849</td>\n",
       "      <td>0</td>\n",
       "      <td>44</td>\n",
       "      <td>2458</td>\n",
       "      <td>1.14</td>\n",
       "      <td>63.86</td>\n",
       "      <td>地区待确认</td>\n",
       "      <td>香港</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>634</td>\n",
       "      <td>716</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>82</td>\n",
       "      <td>0.00</td>\n",
       "      <td>11.45</td>\n",
       "      <td>乌鲁木齐</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>50.00</td>\n",
       "      <td>喀什</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.00</td>\n",
       "      <td>80.00</td>\n",
       "      <td>昌吉州</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>地区待确认</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>10.00</td>\n",
       "      <td>90.00</td>\n",
       "      <td>兵团第四师</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>吐鲁番</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>25.00</td>\n",
       "      <td>75.00</td>\n",
       "      <td>第八师石河子</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>25.00</td>\n",
       "      <td>75.00</td>\n",
       "      <td>兵团第九师</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>伊犁州</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>六师五家渠</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>兵团第十二师</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>巴州</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>第七师</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>阿克苏</td>\n",
       "      <td>新疆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>91</td>\n",
       "      <td>110</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0.00</td>\n",
       "      <td>17.27</td>\n",
       "      <td>大连</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>3</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>0.00</td>\n",
       "      <td>91.18</td>\n",
       "      <td>境外输入</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0.00</td>\n",
       "      <td>87.50</td>\n",
       "      <td>铁岭</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>8.33</td>\n",
       "      <td>91.67</td>\n",
       "      <td>葫芦岛</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>抚顺</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>16.67</td>\n",
       "      <td>83.33</td>\n",
       "      <td>朝阳市</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>丹东</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>沈阳</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>鞍山</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>锦州</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>盘锦</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>阜新</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>本溪</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>辽阳</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>营口</td>\n",
       "      <td>辽宁</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>43</td>\n",
       "      <td>8.51</td>\n",
       "      <td>91.49</td>\n",
       "      <td>绥化</td>\n",
       "      <td>黑龙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>鹤岗</td>\n",
       "      <td>黑龙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>七台河</td>\n",
       "      <td>黑龙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>鸡西</td>\n",
       "      <td>黑龙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>伊春</td>\n",
       "      <td>黑龙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>佳木斯</td>\n",
       "      <td>黑龙江</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>境外输入</td>\n",
       "      <td>宁夏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>银川</td>\n",
       "      <td>宁夏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>吴忠</td>\n",
       "      <td>宁夏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>固原</td>\n",
       "      <td>宁夏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>中卫</td>\n",
       "      <td>宁夏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>石嘴山</td>\n",
       "      <td>宁夏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>宁东管委会</td>\n",
       "      <td>宁夏</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>境外输入</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>宣城</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>池州</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>0</td>\n",
       "      <td>108</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>108</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>亳州</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>0</td>\n",
       "      <td>69</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>六安</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>宿州</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>0</td>\n",
       "      <td>155</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>155</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>阜阳</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>滁州</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>黄山</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>0</td>\n",
       "      <td>83</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>83</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>安庆</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>29</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>铜陵</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>淮北</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>457</th>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>马鞍山</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458</th>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>淮南</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>459</th>\n",
       "      <td>0</td>\n",
       "      <td>160</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>155</td>\n",
       "      <td>3.12</td>\n",
       "      <td>96.88</td>\n",
       "      <td>蚌埠</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>460</th>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>芜湖</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>461</th>\n",
       "      <td>0</td>\n",
       "      <td>174</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>173</td>\n",
       "      <td>0.57</td>\n",
       "      <td>99.43</td>\n",
       "      <td>合肥</td>\n",
       "      <td>安徽</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>462 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     现有确诊  累计确诊  疑似病例  累计死亡  累计治愈   死亡率     治愈率     城市  省份\n",
       "0    1347  3849     0    44  2458  1.14   63.86  地区待确认  香港\n",
       "1     634   716     0     0    82  0.00   11.45   乌鲁木齐  新疆\n",
       "2       1     2     0     0     1  0.00   50.00     喀什  新疆\n",
       "3       1     5     0     0     4  0.00   80.00    昌吉州  新疆\n",
       "4       1     1     0     0     0  0.00    0.00  地区待确认  新疆\n",
       "..    ...   ...   ...   ...   ...   ...     ...    ...  ..\n",
       "457     0    38     0     0    38  0.00  100.00    马鞍山  安徽\n",
       "458     0    27     0     0    27  0.00  100.00     淮南  安徽\n",
       "459     0   160     0     5   155  3.12   96.88     蚌埠  安徽\n",
       "460     0    34     0     0    34  0.00  100.00     芜湖  安徽\n",
       "461     0   174     0     1   173  0.57   99.43     合肥  安徽\n",
       "\n",
       "[462 rows x 9 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#读取数据\n",
    "china_city_data=pd.read_csv('./china_city_data.csv',encoding='gbk')\n",
    "china_city_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 462 entries, 0 to 461\n",
      "Data columns (total 9 columns):\n",
      "现有确诊    462 non-null int64\n",
      "累计确诊    462 non-null int64\n",
      "疑似病例    462 non-null int64\n",
      "累计死亡    462 non-null int64\n",
      "累计治愈    462 non-null int64\n",
      "死亡率     462 non-null float64\n",
      "治愈率     462 non-null float64\n",
      "城市      462 non-null object\n",
      "省份      462 non-null object\n",
      "dtypes: float64(2), int64(5), object(2)\n",
      "memory usage: 32.6+ KB\n"
     ]
    }
   ],
   "source": [
    "###查看各字段的数据类型\n",
    "china_city_data.info()\n",
    "###china_city_data.csv中共含有462条数据，没有数据缺失\n",
    "###数据类型:float64(2), int64(5), object(2),其中'省份','城市'为object型，'死亡率'和'治愈率'为float64型，其余为int64型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>疑似病例</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
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       "      <th>治愈率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>462.000000</td>\n",
       "      <td>462.000000</td>\n",
       "      <td>462.0</td>\n",
       "      <td>462.000000</td>\n",
       "      <td>462.000000</td>\n",
       "      <td>462.000000</td>\n",
       "      <td>462.000000</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.785714</td>\n",
       "      <td>192.424242</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.140693</td>\n",
       "      <td>177.497835</td>\n",
       "      <td>1.228312</td>\n",
       "      <td>113.218398</td>\n",
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       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>71.901170</td>\n",
       "      <td>2360.068404</td>\n",
       "      <td>0.0</td>\n",
       "      <td>180.212840</td>\n",
       "      <td>2176.552825</td>\n",
       "      <td>4.213564</td>\n",
       "      <td>385.556685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-331.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>98.712500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>15.500000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>100.000000</td>\n",
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       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1347.000000</td>\n",
       "      <td>50340.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3869.000000</td>\n",
       "      <td>46471.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>8375.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              现有确诊          累计确诊   疑似病例         累计死亡          累计治愈  \\\n",
       "count   462.000000    462.000000  462.0   462.000000    462.000000   \n",
       "mean      4.785714    192.424242    0.0    10.140693    177.497835   \n",
       "std      71.901170   2360.068404    0.0   180.212840   2176.552825   \n",
       "min    -331.000000      0.000000    0.0     0.000000      0.000000   \n",
       "25%       0.000000      6.000000    0.0     0.000000      6.000000   \n",
       "50%       0.000000     15.500000    0.0     0.000000     15.000000   \n",
       "75%       0.000000     44.000000    0.0     0.000000     43.000000   \n",
       "max    1347.000000  50340.000000    0.0  3869.000000  46471.000000   \n",
       "\n",
       "              死亡率          治愈率  \n",
       "count  462.000000   462.000000  \n",
       "mean     1.228312   113.218398  \n",
       "std      4.213564   385.556685  \n",
       "min      0.000000     0.000000  \n",
       "25%      0.000000    98.712500  \n",
       "50%      0.000000   100.000000  \n",
       "75%      0.000000   100.000000  \n",
       "max     45.000000  8375.000000  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "####查看数据摘要信息\n",
    "china_city_data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 二、全球及海外疫情数据分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##1.海外每天疫情数据分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>死亡率</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>治愈率</th>\n",
       "      <th>新增确诊</th>\n",
       "      <th>日期</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3</td>\n",
       "      <td>5.26</td>\n",
       "      <td>19</td>\n",
       "      <td>01/28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3</td>\n",
       "      <td>4.05</td>\n",
       "      <td>12</td>\n",
       "      <td>01/29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>98</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6</td>\n",
       "      <td>6.12</td>\n",
       "      <td>14</td>\n",
       "      <td>01/30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>124</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>11</td>\n",
       "      <td>8.87</td>\n",
       "      <td>24</td>\n",
       "      <td>01/31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>139</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>11</td>\n",
       "      <td>7.91</td>\n",
       "      <td>26</td>\n",
       "      <td>02/01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>0.67</td>\n",
       "      <td>11</td>\n",
       "      <td>7.38</td>\n",
       "      <td>14</td>\n",
       "      <td>02/02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>154</td>\n",
       "      <td>1</td>\n",
       "      <td>0.65</td>\n",
       "      <td>12</td>\n",
       "      <td>7.79</td>\n",
       "      <td>7</td>\n",
       "      <td>02/03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>177</td>\n",
       "      <td>1</td>\n",
       "      <td>0.56</td>\n",
       "      <td>19</td>\n",
       "      <td>10.73</td>\n",
       "      <td>6</td>\n",
       "      <td>02/04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>201</td>\n",
       "      <td>1</td>\n",
       "      <td>0.50</td>\n",
       "      <td>21</td>\n",
       "      <td>10.45</td>\n",
       "      <td>32</td>\n",
       "      <td>02/05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>225</td>\n",
       "      <td>1</td>\n",
       "      <td>0.44</td>\n",
       "      <td>25</td>\n",
       "      <td>11.11</td>\n",
       "      <td>25</td>\n",
       "      <td>02/06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>273</td>\n",
       "      <td>1</td>\n",
       "      <td>0.37</td>\n",
       "      <td>27</td>\n",
       "      <td>9.89</td>\n",
       "      <td>54</td>\n",
       "      <td>02/07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>299</td>\n",
       "      <td>1</td>\n",
       "      <td>0.33</td>\n",
       "      <td>29</td>\n",
       "      <td>9.70</td>\n",
       "      <td>18</td>\n",
       "      <td>02/08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>313</td>\n",
       "      <td>1</td>\n",
       "      <td>0.32</td>\n",
       "      <td>30</td>\n",
       "      <td>9.58</td>\n",
       "      <td>19</td>\n",
       "      <td>02/09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>385</td>\n",
       "      <td>1</td>\n",
       "      <td>0.26</td>\n",
       "      <td>36</td>\n",
       "      <td>9.35</td>\n",
       "      <td>12</td>\n",
       "      <td>02/10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>397</td>\n",
       "      <td>1</td>\n",
       "      <td>0.25</td>\n",
       "      <td>44</td>\n",
       "      <td>11.08</td>\n",
       "      <td>76</td>\n",
       "      <td>02/11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>444</td>\n",
       "      <td>1</td>\n",
       "      <td>0.23</td>\n",
       "      <td>50</td>\n",
       "      <td>11.26</td>\n",
       "      <td>46</td>\n",
       "      <td>02/12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>505</td>\n",
       "      <td>2</td>\n",
       "      <td>0.40</td>\n",
       "      <td>56</td>\n",
       "      <td>11.09</td>\n",
       "      <td>6</td>\n",
       "      <td>02/13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>516</td>\n",
       "      <td>2</td>\n",
       "      <td>0.39</td>\n",
       "      <td>59</td>\n",
       "      <td>11.43</td>\n",
       "      <td>58</td>\n",
       "      <td>02/14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>601</td>\n",
       "      <td>3</td>\n",
       "      <td>0.50</td>\n",
       "      <td>61</td>\n",
       "      <td>10.15</td>\n",
       "      <td>21</td>\n",
       "      <td>02/15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>687</td>\n",
       "      <td>3</td>\n",
       "      <td>0.44</td>\n",
       "      <td>84</td>\n",
       "      <td>12.23</td>\n",
       "      <td>157</td>\n",
       "      <td>02/16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>800</td>\n",
       "      <td>3</td>\n",
       "      <td>0.38</td>\n",
       "      <td>88</td>\n",
       "      <td>11.00</td>\n",
       "      <td>111</td>\n",
       "      <td>02/17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>904</td>\n",
       "      <td>3</td>\n",
       "      <td>0.33</td>\n",
       "      <td>114</td>\n",
       "      <td>12.61</td>\n",
       "      <td>10</td>\n",
       "      <td>02/18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1018</td>\n",
       "      <td>3</td>\n",
       "      <td>0.29</td>\n",
       "      <td>127</td>\n",
       "      <td>12.48</td>\n",
       "      <td>120</td>\n",
       "      <td>02/19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1096</td>\n",
       "      <td>8</td>\n",
       "      <td>0.73</td>\n",
       "      <td>127</td>\n",
       "      <td>11.59</td>\n",
       "      <td>149</td>\n",
       "      <td>02/20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1231</td>\n",
       "      <td>11</td>\n",
       "      <td>0.89</td>\n",
       "      <td>142</td>\n",
       "      <td>11.54</td>\n",
       "      <td>127</td>\n",
       "      <td>02/21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1528</td>\n",
       "      <td>14</td>\n",
       "      <td>0.92</td>\n",
       "      <td>154</td>\n",
       "      <td>10.08</td>\n",
       "      <td>182</td>\n",
       "      <td>02/22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1895</td>\n",
       "      <td>22</td>\n",
       "      <td>1.16</td>\n",
       "      <td>155</td>\n",
       "      <td>8.18</td>\n",
       "      <td>386</td>\n",
       "      <td>02/23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2286</td>\n",
       "      <td>32</td>\n",
       "      <td>1.40</td>\n",
       "      <td>173</td>\n",
       "      <td>7.57</td>\n",
       "      <td>300</td>\n",
       "      <td>02/24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2575</td>\n",
       "      <td>40</td>\n",
       "      <td>1.55</td>\n",
       "      <td>192</td>\n",
       "      <td>7.46</td>\n",
       "      <td>365</td>\n",
       "      <td>02/25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>3085</td>\n",
       "      <td>51</td>\n",
       "      <td>1.65</td>\n",
       "      <td>220</td>\n",
       "      <td>7.13</td>\n",
       "      <td>459</td>\n",
       "      <td>02/26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>3963715</td>\n",
       "      <td>199665</td>\n",
       "      <td>5.04</td>\n",
       "      <td>1636746</td>\n",
       "      <td>41.29</td>\n",
       "      <td>168936</td>\n",
       "      <td>07/08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>4025946</td>\n",
       "      <td>200559</td>\n",
       "      <td>4.98</td>\n",
       "      <td>1674562</td>\n",
       "      <td>41.59</td>\n",
       "      <td>204934</td>\n",
       "      <td>07/09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>4087556</td>\n",
       "      <td>201524</td>\n",
       "      <td>4.93</td>\n",
       "      <td>1708311</td>\n",
       "      <td>41.79</td>\n",
       "      <td>228056</td>\n",
       "      <td>07/10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>4160195</td>\n",
       "      <td>202375</td>\n",
       "      <td>4.86</td>\n",
       "      <td>1742378</td>\n",
       "      <td>41.88</td>\n",
       "      <td>219941</td>\n",
       "      <td>07/11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>4224055</td>\n",
       "      <td>203106</td>\n",
       "      <td>4.81</td>\n",
       "      <td>1771303</td>\n",
       "      <td>41.93</td>\n",
       "      <td>230335</td>\n",
       "      <td>07/12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>4282404</td>\n",
       "      <td>203486</td>\n",
       "      <td>4.75</td>\n",
       "      <td>1798967</td>\n",
       "      <td>42.01</td>\n",
       "      <td>215493</td>\n",
       "      <td>07/13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>4349937</td>\n",
       "      <td>203954</td>\n",
       "      <td>4.69</td>\n",
       "      <td>1831352</td>\n",
       "      <td>42.10</td>\n",
       "      <td>196720</td>\n",
       "      <td>07/14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>4416197</td>\n",
       "      <td>204853</td>\n",
       "      <td>4.64</td>\n",
       "      <td>1882078</td>\n",
       "      <td>42.62</td>\n",
       "      <td>185782</td>\n",
       "      <td>07/15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>4488822</td>\n",
       "      <td>205858</td>\n",
       "      <td>4.59</td>\n",
       "      <td>1927845</td>\n",
       "      <td>42.95</td>\n",
       "      <td>226161</td>\n",
       "      <td>07/16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>4568381</td>\n",
       "      <td>206835</td>\n",
       "      <td>4.53</td>\n",
       "      <td>1961516</td>\n",
       "      <td>42.94</td>\n",
       "      <td>237665</td>\n",
       "      <td>07/17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>4644768</td>\n",
       "      <td>207785</td>\n",
       "      <td>4.47</td>\n",
       "      <td>2023116</td>\n",
       "      <td>43.56</td>\n",
       "      <td>259766</td>\n",
       "      <td>07/18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>4708027</td>\n",
       "      <td>208598</td>\n",
       "      <td>4.43</td>\n",
       "      <td>2057102</td>\n",
       "      <td>43.69</td>\n",
       "      <td>166655</td>\n",
       "      <td>07/19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>4773306</td>\n",
       "      <td>209010</td>\n",
       "      <td>4.38</td>\n",
       "      <td>2084221</td>\n",
       "      <td>43.66</td>\n",
       "      <td>229649</td>\n",
       "      <td>07/20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>4840766</td>\n",
       "      <td>209557</td>\n",
       "      <td>4.33</td>\n",
       "      <td>2131872</td>\n",
       "      <td>44.04</td>\n",
       "      <td>213553</td>\n",
       "      <td>07/21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>4909264</td>\n",
       "      <td>210678</td>\n",
       "      <td>4.29</td>\n",
       "      <td>2168466</td>\n",
       "      <td>44.17</td>\n",
       "      <td>202652</td>\n",
       "      <td>07/22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>4982927</td>\n",
       "      <td>211910</td>\n",
       "      <td>4.25</td>\n",
       "      <td>2224520</td>\n",
       "      <td>44.64</td>\n",
       "      <td>247090</td>\n",
       "      <td>07/23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>5054985</td>\n",
       "      <td>213079</td>\n",
       "      <td>4.22</td>\n",
       "      <td>2261500</td>\n",
       "      <td>44.74</td>\n",
       "      <td>284057</td>\n",
       "      <td>07/24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>5135249</td>\n",
       "      <td>214223</td>\n",
       "      <td>4.17</td>\n",
       "      <td>2309957</td>\n",
       "      <td>44.98</td>\n",
       "      <td>283923</td>\n",
       "      <td>07/25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>5202631</td>\n",
       "      <td>215131</td>\n",
       "      <td>4.14</td>\n",
       "      <td>2343575</td>\n",
       "      <td>45.05</td>\n",
       "      <td>200446</td>\n",
       "      <td>07/26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>5258761</td>\n",
       "      <td>215582</td>\n",
       "      <td>4.10</td>\n",
       "      <td>2372012</td>\n",
       "      <td>45.11</td>\n",
       "      <td>254085</td>\n",
       "      <td>07/27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>5326693</td>\n",
       "      <td>216179</td>\n",
       "      <td>4.06</td>\n",
       "      <td>2418486</td>\n",
       "      <td>45.40</td>\n",
       "      <td>226566</td>\n",
       "      <td>07/28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>5393454</td>\n",
       "      <td>218057</td>\n",
       "      <td>4.04</td>\n",
       "      <td>2467777</td>\n",
       "      <td>45.76</td>\n",
       "      <td>214915</td>\n",
       "      <td>07/29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>5398258</td>\n",
       "      <td>218097</td>\n",
       "      <td>4.04</td>\n",
       "      <td>2468150</td>\n",
       "      <td>45.72</td>\n",
       "      <td>253570</td>\n",
       "      <td>07/30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>5534916</td>\n",
       "      <td>221029</td>\n",
       "      <td>3.99</td>\n",
       "      <td>2566848</td>\n",
       "      <td>46.38</td>\n",
       "      <td>292251</td>\n",
       "      <td>07/31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>5608912</td>\n",
       "      <td>222493</td>\n",
       "      <td>3.97</td>\n",
       "      <td>2609455</td>\n",
       "      <td>46.52</td>\n",
       "      <td>289155</td>\n",
       "      <td>08/01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>6088672</td>\n",
       "      <td>243034</td>\n",
       "      <td>3.99</td>\n",
       "      <td>2935605</td>\n",
       "      <td>48.21</td>\n",
       "      <td>262749</td>\n",
       "      <td>08/02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>6138001</td>\n",
       "      <td>243501</td>\n",
       "      <td>3.97</td>\n",
       "      <td>2952919</td>\n",
       "      <td>48.11</td>\n",
       "      <td>257519</td>\n",
       "      <td>08/03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>6195060</td>\n",
       "      <td>244092</td>\n",
       "      <td>3.94</td>\n",
       "      <td>3019500</td>\n",
       "      <td>48.74</td>\n",
       "      <td>219748</td>\n",
       "      <td>08/04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>6257066</td>\n",
       "      <td>245479</td>\n",
       "      <td>3.92</td>\n",
       "      <td>3054382</td>\n",
       "      <td>48.81</td>\n",
       "      <td>206600</td>\n",
       "      <td>08/05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>6315167</td>\n",
       "      <td>246791</td>\n",
       "      <td>3.91</td>\n",
       "      <td>3112839</td>\n",
       "      <td>49.29</td>\n",
       "      <td>0</td>\n",
       "      <td>08/06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>183 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        累计确诊    累计死亡   死亡率     累计治愈    治愈率    新增确诊     日期\n",
       "0         57       0  0.00        3   5.26      19  01/28\n",
       "1         74       0  0.00        3   4.05      12  01/29\n",
       "2         98       0  0.00        6   6.12      14  01/30\n",
       "3        124       0  0.00       11   8.87      24  01/31\n",
       "4        139       0  0.00       11   7.91      26  02/01\n",
       "..       ...     ...   ...      ...    ...     ...    ...\n",
       "178  6088672  243034  3.99  2935605  48.21  262749  08/02\n",
       "179  6138001  243501  3.97  2952919  48.11  257519  08/03\n",
       "180  6195060  244092  3.94  3019500  48.74  219748  08/04\n",
       "181  6257066  245479  3.92  3054382  48.81  206600  08/05\n",
       "182  6315167  246791  3.91  3112839  49.29       0  08/06\n",
       "\n",
       "[183 rows x 7 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##读取数据\n",
    "foreign_daily_data=pd.read_csv('./foreign_daily_data.csv',encoding='gbk')\n",
    "foreign_daily_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 183 entries, 0 to 182\n",
      "Data columns (total 7 columns):\n",
      "累计确诊    183 non-null int64\n",
      "累计死亡    183 non-null int64\n",
      "死亡率     183 non-null float64\n",
      "累计治愈    183 non-null int64\n",
      "治愈率     183 non-null float64\n",
      "新增确诊    183 non-null int64\n",
      "日期      183 non-null object\n",
      "dtypes: float64(2), int64(4), object(1)\n",
      "memory usage: 10.1+ KB\n"
     ]
    }
   ],
   "source": [
    "###查看各字段的数据类型\n",
    "foreign_daily_data.info()\n",
    "##foreign_daily_data.csv中共含有183条数据，没有数据缺失\n",
    "##数据类型：dtypes: float64(2), int64(4), object(1)，'日期'数据类型为object，'死亡率'和'治愈率'数据类型为float64，其他数据类型均为int64"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>死亡率</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>治愈率</th>\n",
       "      <th>新增确诊</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.830000e+02</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>1.830000e+02</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>183.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.032806e+06</td>\n",
       "      <td>108277.295082</td>\n",
       "      <td>4.354973</td>\n",
       "      <td>7.379341e+05</td>\n",
       "      <td>24.133388</td>\n",
       "      <td>94863.743169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.813309e+06</td>\n",
       "      <td>87063.345560</td>\n",
       "      <td>2.127913</td>\n",
       "      <td>8.352804e+05</td>\n",
       "      <td>14.285026</td>\n",
       "      <td>81411.097164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.700000e+01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>4.050000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.295350e+04</td>\n",
       "      <td>2149.000000</td>\n",
       "      <td>3.395000</td>\n",
       "      <td>7.245500e+03</td>\n",
       "      <td>11.080000</td>\n",
       "      <td>7093.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.084195e+06</td>\n",
       "      <td>137957.000000</td>\n",
       "      <td>4.880000</td>\n",
       "      <td>4.572650e+05</td>\n",
       "      <td>21.940000</td>\n",
       "      <td>84313.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.204224e+06</td>\n",
       "      <td>187737.000000</td>\n",
       "      <td>6.160000</td>\n",
       "      <td>1.258531e+06</td>\n",
       "      <td>39.260000</td>\n",
       "      <td>142537.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>6.315167e+06</td>\n",
       "      <td>246791.000000</td>\n",
       "      <td>6.630000</td>\n",
       "      <td>3.112839e+06</td>\n",
       "      <td>49.290000</td>\n",
       "      <td>292251.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               累计确诊           累计死亡         死亡率          累计治愈         治愈率  \\\n",
       "count  1.830000e+02     183.000000  183.000000  1.830000e+02  183.000000   \n",
       "mean   2.032806e+06  108277.295082    4.354973  7.379341e+05   24.133388   \n",
       "std    1.813309e+06   87063.345560    2.127913  8.352804e+05   14.285026   \n",
       "min    5.700000e+01       0.000000    0.000000  3.000000e+00    4.050000   \n",
       "25%    6.295350e+04    2149.000000    3.395000  7.245500e+03   11.080000   \n",
       "50%    2.084195e+06  137957.000000    4.880000  4.572650e+05   21.940000   \n",
       "75%    3.204224e+06  187737.000000    6.160000  1.258531e+06   39.260000   \n",
       "max    6.315167e+06  246791.000000    6.630000  3.112839e+06   49.290000   \n",
       "\n",
       "                新增确诊  \n",
       "count     183.000000  \n",
       "mean    94863.743169  \n",
       "std     81411.097164  \n",
       "min         0.000000  \n",
       "25%      7093.500000  \n",
       "50%     84313.000000  \n",
       "75%    142537.000000  \n",
       "max    292251.000000  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "####查看数据摘要信息\n",
    "foreign_daily_data.describe()\n",
    "###由数据摘要信息可以看出，海外从1月28日到8月6日，平均每天新增确诊人数约为94863人，新增确诊最高一天的人数为292251人\n",
    "##从25%到75%的数据可以看出，累计死亡人数从2149人增加到187737人，说明海外疫情正在迅速蔓延扩散，死亡率也从3.39%增加到6.16%，说明疫情的严重性，以及海外对于疫情的治疗并未取得较好的效果。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##2.全球各国爬取当天疫情数据（含中国）分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>新增确诊</th>\n",
       "      <th>新增死亡</th>\n",
       "      <th>新增治愈</th>\n",
       "      <th>疑似病例</th>\n",
       "      <th>国家</th>\n",
       "      <th>洲名</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2211</td>\n",
       "      <td>88900</td>\n",
       "      <td>4685</td>\n",
       "      <td>82004</td>\n",
       "      <td>218</td>\n",
       "      <td>2</td>\n",
       "      <td>329</td>\n",
       "      <td>2</td>\n",
       "      <td>中国</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2271830</td>\n",
       "      <td>4973568</td>\n",
       "      <td>161601</td>\n",
       "      <td>2540137</td>\n",
       "      <td>55148</td>\n",
       "      <td>1311</td>\n",
       "      <td>58457</td>\n",
       "      <td>0</td>\n",
       "      <td>美国</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>571456</td>\n",
       "      <td>2859073</td>\n",
       "      <td>97256</td>\n",
       "      <td>2190361</td>\n",
       "      <td>57152</td>\n",
       "      <td>1437</td>\n",
       "      <td>32808</td>\n",
       "      <td>0</td>\n",
       "      <td>巴西</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>595501</td>\n",
       "      <td>1964536</td>\n",
       "      <td>40699</td>\n",
       "      <td>1328336</td>\n",
       "      <td>56282</td>\n",
       "      <td>904</td>\n",
       "      <td>46121</td>\n",
       "      <td>0</td>\n",
       "      <td>印度</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>180539</td>\n",
       "      <td>870187</td>\n",
       "      <td>14579</td>\n",
       "      <td>675069</td>\n",
       "      <td>5239</td>\n",
       "      <td>114</td>\n",
       "      <td>7300</td>\n",
       "      <td>0</td>\n",
       "      <td>俄罗斯</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>143313</td>\n",
       "      <td>529877</td>\n",
       "      <td>9298</td>\n",
       "      <td>377266</td>\n",
       "      <td>8559</td>\n",
       "      <td>414</td>\n",
       "      <td>13515</td>\n",
       "      <td>0</td>\n",
       "      <td>南非</td>\n",
       "      <td>非洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>44638</td>\n",
       "      <td>456100</td>\n",
       "      <td>49698</td>\n",
       "      <td>361764</td>\n",
       "      <td>6139</td>\n",
       "      <td>829</td>\n",
       "      <td>4320</td>\n",
       "      <td>0</td>\n",
       "      <td>墨西哥</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>120966</td>\n",
       "      <td>447624</td>\n",
       "      <td>20228</td>\n",
       "      <td>306430</td>\n",
       "      <td>7734</td>\n",
       "      <td>221</td>\n",
       "      <td>3973</td>\n",
       "      <td>0</td>\n",
       "      <td>秘鲁</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>16640</td>\n",
       "      <td>364723</td>\n",
       "      <td>9792</td>\n",
       "      <td>338291</td>\n",
       "      <td>1761</td>\n",
       "      <td>47</td>\n",
       "      <td>1961</td>\n",
       "      <td>0</td>\n",
       "      <td>智利</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>127390</td>\n",
       "      <td>352847</td>\n",
       "      <td>28499</td>\n",
       "      <td>196958</td>\n",
       "      <td>2953</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>西班牙</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>147773</td>\n",
       "      <td>345714</td>\n",
       "      <td>11624</td>\n",
       "      <td>186317</td>\n",
       "      <td>10735</td>\n",
       "      <td>309</td>\n",
       "      <td>6059</td>\n",
       "      <td>0</td>\n",
       "      <td>哥伦比亚</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>24678</td>\n",
       "      <td>320117</td>\n",
       "      <td>17976</td>\n",
       "      <td>277463</td>\n",
       "      <td>2634</td>\n",
       "      <td>174</td>\n",
       "      <td>2531</td>\n",
       "      <td>0</td>\n",
       "      <td>伊朗</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>259530</td>\n",
       "      <td>307272</td>\n",
       "      <td>46295</td>\n",
       "      <td>1447</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>英国</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>34082</td>\n",
       "      <td>284226</td>\n",
       "      <td>3055</td>\n",
       "      <td>247089</td>\n",
       "      <td>1402</td>\n",
       "      <td>35</td>\n",
       "      <td>1775</td>\n",
       "      <td>0</td>\n",
       "      <td>沙特阿拉伯</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>19770</td>\n",
       "      <td>281863</td>\n",
       "      <td>6035</td>\n",
       "      <td>256058</td>\n",
       "      <td>727</td>\n",
       "      <td>21</td>\n",
       "      <td>1772</td>\n",
       "      <td>0</td>\n",
       "      <td>巴基斯坦</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>102521</td>\n",
       "      <td>249651</td>\n",
       "      <td>3306</td>\n",
       "      <td>143824</td>\n",
       "      <td>2977</td>\n",
       "      <td>39</td>\n",
       "      <td>2074</td>\n",
       "      <td>0</td>\n",
       "      <td>孟加拉</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>12646</td>\n",
       "      <td>248803</td>\n",
       "      <td>35181</td>\n",
       "      <td>200976</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>意大利</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10822</td>\n",
       "      <td>236112</td>\n",
       "      <td>5784</td>\n",
       "      <td>219506</td>\n",
       "      <td>1178</td>\n",
       "      <td>19</td>\n",
       "      <td>1015</td>\n",
       "      <td>0</td>\n",
       "      <td>土耳其</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>118410</td>\n",
       "      <td>231310</td>\n",
       "      <td>30308</td>\n",
       "      <td>82592</td>\n",
       "      <td>2734</td>\n",
       "      <td>11</td>\n",
       "      <td>828</td>\n",
       "      <td>0</td>\n",
       "      <td>法国</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>116695</td>\n",
       "      <td>220682</td>\n",
       "      <td>4135</td>\n",
       "      <td>99852</td>\n",
       "      <td>7147</td>\n",
       "      <td>126</td>\n",
       "      <td>2904</td>\n",
       "      <td>0</td>\n",
       "      <td>阿根廷</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10168</td>\n",
       "      <td>214496</td>\n",
       "      <td>9180</td>\n",
       "      <td>195148</td>\n",
       "      <td>1060</td>\n",
       "      <td>7</td>\n",
       "      <td>692</td>\n",
       "      <td>0</td>\n",
       "      <td>德国</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>34417</td>\n",
       "      <td>140603</td>\n",
       "      <td>5161</td>\n",
       "      <td>101025</td>\n",
       "      <td>3047</td>\n",
       "      <td>67</td>\n",
       "      <td>2583</td>\n",
       "      <td>0</td>\n",
       "      <td>伊拉克</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>6646</td>\n",
       "      <td>120033</td>\n",
       "      <td>9010</td>\n",
       "      <td>104377</td>\n",
       "      <td>374</td>\n",
       "      <td>5</td>\n",
       "      <td>319</td>\n",
       "      <td>0</td>\n",
       "      <td>加拿大</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>50473</td>\n",
       "      <td>119460</td>\n",
       "      <td>2150</td>\n",
       "      <td>66837</td>\n",
       "      <td>3480</td>\n",
       "      <td>27</td>\n",
       "      <td>567</td>\n",
       "      <td>0</td>\n",
       "      <td>菲律宾</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>37587</td>\n",
       "      <td>118753</td>\n",
       "      <td>5521</td>\n",
       "      <td>75645</td>\n",
       "      <td>1882</td>\n",
       "      <td>69</td>\n",
       "      <td>1756</td>\n",
       "      <td>0</td>\n",
       "      <td>印度尼西亚</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>3083</td>\n",
       "      <td>112092</td>\n",
       "      <td>178</td>\n",
       "      <td>108831</td>\n",
       "      <td>554</td>\n",
       "      <td>1</td>\n",
       "      <td>577</td>\n",
       "      <td>0</td>\n",
       "      <td>卡塔尔</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26013</td>\n",
       "      <td>95942</td>\n",
       "      <td>1058</td>\n",
       "      <td>68871</td>\n",
       "      <td>1060</td>\n",
       "      <td>0</td>\n",
       "      <td>1840</td>\n",
       "      <td>0</td>\n",
       "      <td>哈萨克斯坦</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>42763</td>\n",
       "      <td>94875</td>\n",
       "      <td>4930</td>\n",
       "      <td>47182</td>\n",
       "      <td>123</td>\n",
       "      <td>18</td>\n",
       "      <td>1613</td>\n",
       "      <td>0</td>\n",
       "      <td>埃及</td>\n",
       "      <td>非洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>11851</td>\n",
       "      <td>88866</td>\n",
       "      <td>5847</td>\n",
       "      <td>71168</td>\n",
       "      <td>903</td>\n",
       "      <td>39</td>\n",
       "      <td>183</td>\n",
       "      <td>0</td>\n",
       "      <td>厄瓜多尔</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>55319</td>\n",
       "      <td>85141</td>\n",
       "      <td>3385</td>\n",
       "      <td>26437</td>\n",
       "      <td>1780</td>\n",
       "      <td>65</td>\n",
       "      <td>1047</td>\n",
       "      <td>0</td>\n",
       "      <td>玻利维亚</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>0</td>\n",
       "      <td>699</td>\n",
       "      <td>42</td>\n",
       "      <td>657</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>圣马力诺</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>298</td>\n",
       "      <td>509</td>\n",
       "      <td>22</td>\n",
       "      <td>189</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>圭亚那</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>305</td>\n",
       "      <td>509</td>\n",
       "      <td>21</td>\n",
       "      <td>183</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>坦桑尼亚</td>\n",
       "      <td>非洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>90</td>\n",
       "      <td>395</td>\n",
       "      <td>1</td>\n",
       "      <td>304</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>布隆迪</td>\n",
       "      <td>非洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>41</td>\n",
       "      <td>388</td>\n",
       "      <td>7</td>\n",
       "      <td>340</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>科摩罗</td>\n",
       "      <td>非洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>43</td>\n",
       "      <td>357</td>\n",
       "      <td>6</td>\n",
       "      <td>308</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>缅甸</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>0</td>\n",
       "      <td>344</td>\n",
       "      <td>10</td>\n",
       "      <td>334</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>毛里求斯</td>\n",
       "      <td>非洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>33</td>\n",
       "      <td>293</td>\n",
       "      <td>0</td>\n",
       "      <td>260</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>蒙古</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>57</td>\n",
       "      <td>282</td>\n",
       "      <td>0</td>\n",
       "      <td>225</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>厄立特里亚</td>\n",
       "      <td>非洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>33</td>\n",
       "      <td>243</td>\n",
       "      <td>0</td>\n",
       "      <td>210</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>柬埔寨</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>64</td>\n",
       "      <td>207</td>\n",
       "      <td>8</td>\n",
       "      <td>135</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>特立尼达和多巴哥</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>107</td>\n",
       "      <td>163</td>\n",
       "      <td>3</td>\n",
       "      <td>53</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>巴布亚新几内亚</td>\n",
       "      <td>大洋洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>0</td>\n",
       "      <td>141</td>\n",
       "      <td>3</td>\n",
       "      <td>138</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>文莱</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>26</td>\n",
       "      <td>133</td>\n",
       "      <td>7</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>巴巴多斯</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>2</td>\n",
       "      <td>126</td>\n",
       "      <td>0</td>\n",
       "      <td>124</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>塞舌尔</td>\n",
       "      <td>非洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>16</td>\n",
       "      <td>125</td>\n",
       "      <td>4</td>\n",
       "      <td>105</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>摩纳哥</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>12</td>\n",
       "      <td>105</td>\n",
       "      <td>0</td>\n",
       "      <td>93</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>不丹</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>13</td>\n",
       "      <td>92</td>\n",
       "      <td>3</td>\n",
       "      <td>76</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>安提瓜和巴布达</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>3</td>\n",
       "      <td>89</td>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>列支敦士登公国</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>53</td>\n",
       "      <td>86</td>\n",
       "      <td>2</td>\n",
       "      <td>31</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>伯利兹</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>10</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>圣文森特和格林纳丁斯</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>36</td>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>马提尼克岛</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>8</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>斐济</td>\n",
       "      <td>大洋洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>东帝汶</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>圣卢西亚</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>格林纳达</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>老挝</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>多米尼克</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>圣基茨和尼维斯</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>梵蒂冈</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>183 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        现有确诊     累计确诊    累计死亡     累计治愈   新增确诊  新增死亡   新增治愈  疑似病例       国家   洲名\n",
       "0       2211    88900    4685    82004    218     2    329     2       中国   亚洲\n",
       "1    2271830  4973568  161601  2540137  55148  1311  58457     0       美国  北美洲\n",
       "2     571456  2859073   97256  2190361  57152  1437  32808     0       巴西  南美洲\n",
       "3     595501  1964536   40699  1328336  56282   904  46121     0       印度   亚洲\n",
       "4     180539   870187   14579   675069   5239   114   7300     0      俄罗斯   欧洲\n",
       "..       ...      ...     ...      ...    ...   ...    ...   ...      ...  ...\n",
       "178        1       24       0       23      0     0      0     0     格林纳达  北美洲\n",
       "179        1       20       0       19      0     0      0     0       老挝   亚洲\n",
       "180        0       18       0       18      0     0      0     0     多米尼克  北美洲\n",
       "181        1       17       0       16      0     0      0     0  圣基茨和尼维斯  北美洲\n",
       "182        0       12       0       12      0     0      0     0      梵蒂冈   欧洲\n",
       "\n",
       "[183 rows x 10 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##读取数据\n",
    "world_country_data=pd.read_csv('./world_country_data.csv',encoding='gbk')\n",
    "world_country_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 183 entries, 0 to 182\n",
      "Data columns (total 10 columns):\n",
      "现有确诊    183 non-null int64\n",
      "累计确诊    183 non-null int64\n",
      "累计死亡    183 non-null int64\n",
      "累计治愈    183 non-null int64\n",
      "新增确诊    183 non-null int64\n",
      "新增死亡    183 non-null int64\n",
      "新增治愈    183 non-null int64\n",
      "疑似病例    183 non-null int64\n",
      "国家      183 non-null object\n",
      "洲名      182 non-null object\n",
      "dtypes: int64(8), object(2)\n",
      "memory usage: 14.4+ KB\n"
     ]
    }
   ],
   "source": [
    "###查看各字段的数据类型\n",
    "world_country_data.info()\n",
    "####world_country_data.csv中共有183条数据，而'洲名'字段只有182条数据  ，特立尼达和多巴哥的洲名为NAN\n",
    "###数据类型：int64(8), object(2)，除'国家'和'洲名'是object型，其他字段都是int64型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>新增确诊</th>\n",
       "      <th>新增死亡</th>\n",
       "      <th>新增治愈</th>\n",
       "      <th>疑似病例</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.830000e+02</td>\n",
       "      <td>1.830000e+02</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>1.830000e+02</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>183.000000</td>\n",
       "      <td>183.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.226738e+04</td>\n",
       "      <td>1.040057e+05</td>\n",
       "      <td>3887.759563</td>\n",
       "      <td>6.785060e+04</td>\n",
       "      <td>1475.688525</td>\n",
       "      <td>37.005464</td>\n",
       "      <td>1242.065574</td>\n",
       "      <td>0.010929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.799995e+05</td>\n",
       "      <td>4.540187e+05</td>\n",
       "      <td>15540.206434</td>\n",
       "      <td>2.739627e+05</td>\n",
       "      <td>7237.090729</td>\n",
       "      <td>172.987502</td>\n",
       "      <td>6111.594402</td>\n",
       "      <td>0.147844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.200000e+01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.175000e+02</td>\n",
       "      <td>1.214500e+03</td>\n",
       "      <td>21.500000</td>\n",
       "      <td>8.030000e+02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.471000e+03</td>\n",
       "      <td>7.007000e+03</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>4.839000e+03</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9.858000e+03</td>\n",
       "      <td>4.730650e+04</td>\n",
       "      <td>980.500000</td>\n",
       "      <td>2.968700e+04</td>\n",
       "      <td>394.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>316.500000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.271830e+06</td>\n",
       "      <td>4.973568e+06</td>\n",
       "      <td>161601.000000</td>\n",
       "      <td>2.540137e+06</td>\n",
       "      <td>57152.000000</td>\n",
       "      <td>1437.000000</td>\n",
       "      <td>58457.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               现有确诊          累计确诊           累计死亡          累计治愈          新增确诊  \\\n",
       "count  1.830000e+02  1.830000e+02     183.000000  1.830000e+02    183.000000   \n",
       "mean   3.226738e+04  1.040057e+05    3887.759563  6.785060e+04   1475.688525   \n",
       "std    1.799995e+05  4.540187e+05   15540.206434  2.739627e+05   7237.090729   \n",
       "min    0.000000e+00  1.200000e+01       0.000000  0.000000e+00      0.000000   \n",
       "25%    2.175000e+02  1.214500e+03      21.500000  8.030000e+02      0.000000   \n",
       "50%    1.471000e+03  7.007000e+03     125.000000  4.839000e+03     43.000000   \n",
       "75%    9.858000e+03  4.730650e+04     980.500000  2.968700e+04    394.000000   \n",
       "max    2.271830e+06  4.973568e+06  161601.000000  2.540137e+06  57152.000000   \n",
       "\n",
       "              新增死亡          新增治愈        疑似病例  \n",
       "count   183.000000    183.000000  183.000000  \n",
       "mean     37.005464   1242.065574    0.010929  \n",
       "std     172.987502   6111.594402    0.147844  \n",
       "min       0.000000      0.000000    0.000000  \n",
       "25%       0.000000      0.000000    0.000000  \n",
       "50%       0.000000     21.000000    0.000000  \n",
       "75%       5.000000    316.500000    0.000000  \n",
       "max    1437.000000  58457.000000    2.000000  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "####查看数据摘要信息\n",
    "world_country_data.describe()\n",
    "###从数据摘要信息看，全球比上一天新增确诊平均数约为1476，新增死亡平均数约为37，新增治愈平均数约为1242\n",
    "###全球国家现有确诊最高为2271830人，累计确诊最高为4973568人，累计死亡最高为161601人，累计治愈最高为2540137人\n",
    "###全球国家新增确诊最高为57152人，新增死亡最高为1437人，新增治愈最高为58457人"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>新增确诊</th>\n",
       "      <th>新增死亡</th>\n",
       "      <th>新增治愈</th>\n",
       "      <th>疑似病例</th>\n",
       "      <th>国家</th>\n",
       "      <th>洲名</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2271830</td>\n",
       "      <td>4973568</td>\n",
       "      <td>161601</td>\n",
       "      <td>2540137</td>\n",
       "      <td>55148</td>\n",
       "      <td>1311</td>\n",
       "      <td>58457</td>\n",
       "      <td>0</td>\n",
       "      <td>美国</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>595501</td>\n",
       "      <td>1964536</td>\n",
       "      <td>40699</td>\n",
       "      <td>1328336</td>\n",
       "      <td>56282</td>\n",
       "      <td>904</td>\n",
       "      <td>46121</td>\n",
       "      <td>0</td>\n",
       "      <td>印度</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>571456</td>\n",
       "      <td>2859073</td>\n",
       "      <td>97256</td>\n",
       "      <td>2190361</td>\n",
       "      <td>57152</td>\n",
       "      <td>1437</td>\n",
       "      <td>32808</td>\n",
       "      <td>0</td>\n",
       "      <td>巴西</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>259530</td>\n",
       "      <td>307272</td>\n",
       "      <td>46295</td>\n",
       "      <td>1447</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>英国</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>180539</td>\n",
       "      <td>870187</td>\n",
       "      <td>14579</td>\n",
       "      <td>675069</td>\n",
       "      <td>5239</td>\n",
       "      <td>114</td>\n",
       "      <td>7300</td>\n",
       "      <td>0</td>\n",
       "      <td>俄罗斯</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       现有确诊     累计确诊    累计死亡     累计治愈   新增确诊  新增死亡   新增治愈  疑似病例   国家   洲名\n",
       "1   2271830  4973568  161601  2540137  55148  1311  58457     0   美国  北美洲\n",
       "3    595501  1964536   40699  1328336  56282   904  46121     0   印度   亚洲\n",
       "2    571456  2859073   97256  2190361  57152  1437  32808     0   巴西  南美洲\n",
       "12   259530   307272   46295     1447     14     0      2     0   英国   欧洲\n",
       "4    180539   870187   14579   675069   5239   114   7300     0  俄罗斯   欧洲"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##全球各国'现有确诊'人数前5的国家数据\n",
    "world_country_data.reindex(world_country_data['现有确诊'].sort_values(ascending=False).index)[:5]\n",
    "##从排序结果可以看出，现有确诊人数前5名国家，北美洲1个，亚洲1个，南美洲1个，欧洲2个\n",
    "###分别是美国 2271830人，印度 595501人，巴西 571456人，英国 259530人，俄罗斯 180539人"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>新增确诊</th>\n",
       "      <th>新增死亡</th>\n",
       "      <th>新增治愈</th>\n",
       "      <th>疑似病例</th>\n",
       "      <th>国家</th>\n",
       "      <th>洲名</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>571456</td>\n",
       "      <td>2859073</td>\n",
       "      <td>97256</td>\n",
       "      <td>2190361</td>\n",
       "      <td>57152</td>\n",
       "      <td>1437</td>\n",
       "      <td>32808</td>\n",
       "      <td>0</td>\n",
       "      <td>巴西</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>595501</td>\n",
       "      <td>1964536</td>\n",
       "      <td>40699</td>\n",
       "      <td>1328336</td>\n",
       "      <td>56282</td>\n",
       "      <td>904</td>\n",
       "      <td>46121</td>\n",
       "      <td>0</td>\n",
       "      <td>印度</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2271830</td>\n",
       "      <td>4973568</td>\n",
       "      <td>161601</td>\n",
       "      <td>2540137</td>\n",
       "      <td>55148</td>\n",
       "      <td>1311</td>\n",
       "      <td>58457</td>\n",
       "      <td>0</td>\n",
       "      <td>美国</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>147773</td>\n",
       "      <td>345714</td>\n",
       "      <td>11624</td>\n",
       "      <td>186317</td>\n",
       "      <td>10735</td>\n",
       "      <td>309</td>\n",
       "      <td>6059</td>\n",
       "      <td>0</td>\n",
       "      <td>哥伦比亚</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>143313</td>\n",
       "      <td>529877</td>\n",
       "      <td>9298</td>\n",
       "      <td>377266</td>\n",
       "      <td>8559</td>\n",
       "      <td>414</td>\n",
       "      <td>13515</td>\n",
       "      <td>0</td>\n",
       "      <td>南非</td>\n",
       "      <td>非洲</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       现有确诊     累计确诊    累计死亡     累计治愈   新增确诊  新增死亡   新增治愈  疑似病例    国家   洲名\n",
       "2    571456  2859073   97256  2190361  57152  1437  32808     0    巴西  南美洲\n",
       "3    595501  1964536   40699  1328336  56282   904  46121     0    印度   亚洲\n",
       "1   2271830  4973568  161601  2540137  55148  1311  58457     0    美国  北美洲\n",
       "10   147773   345714   11624   186317  10735   309   6059     0  哥伦比亚  南美洲\n",
       "5    143313   529877    9298   377266   8559   414  13515     0    南非   非洲"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##全球各国昨日'新增确诊'人数前5的国家数据\n",
    "world_country_data.reindex(world_country_data['新增确诊'].sort_values(ascending=False).index)[:5]\n",
    "###巴西以57152人的数据位居第一，后面是印度 56282人，美国55148人，哥伦比亚 10735人，南非 8559人"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>现有确诊</th>\n",
       "      <th>累计确诊</th>\n",
       "      <th>累计死亡</th>\n",
       "      <th>累计治愈</th>\n",
       "      <th>新增确诊</th>\n",
       "      <th>新增死亡</th>\n",
       "      <th>新增治愈</th>\n",
       "      <th>疑似病例</th>\n",
       "      <th>国家</th>\n",
       "      <th>洲名</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2271830</td>\n",
       "      <td>4973568</td>\n",
       "      <td>161601</td>\n",
       "      <td>2540137</td>\n",
       "      <td>55148</td>\n",
       "      <td>1311</td>\n",
       "      <td>58457</td>\n",
       "      <td>0</td>\n",
       "      <td>美国</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>571456</td>\n",
       "      <td>2859073</td>\n",
       "      <td>97256</td>\n",
       "      <td>2190361</td>\n",
       "      <td>57152</td>\n",
       "      <td>1437</td>\n",
       "      <td>32808</td>\n",
       "      <td>0</td>\n",
       "      <td>巴西</td>\n",
       "      <td>南美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>44638</td>\n",
       "      <td>456100</td>\n",
       "      <td>49698</td>\n",
       "      <td>361764</td>\n",
       "      <td>6139</td>\n",
       "      <td>829</td>\n",
       "      <td>4320</td>\n",
       "      <td>0</td>\n",
       "      <td>墨西哥</td>\n",
       "      <td>北美洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>259530</td>\n",
       "      <td>307272</td>\n",
       "      <td>46295</td>\n",
       "      <td>1447</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>英国</td>\n",
       "      <td>欧洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>595501</td>\n",
       "      <td>1964536</td>\n",
       "      <td>40699</td>\n",
       "      <td>1328336</td>\n",
       "      <td>56282</td>\n",
       "      <td>904</td>\n",
       "      <td>46121</td>\n",
       "      <td>0</td>\n",
       "      <td>印度</td>\n",
       "      <td>亚洲</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       现有确诊     累计确诊    累计死亡     累计治愈   新增确诊  新增死亡   新增治愈  疑似病例   国家   洲名\n",
       "1   2271830  4973568  161601  2540137  55148  1311  58457     0   美国  北美洲\n",
       "2    571456  2859073   97256  2190361  57152  1437  32808     0   巴西  南美洲\n",
       "6     44638   456100   49698   361764   6139   829   4320     0  墨西哥  北美洲\n",
       "12   259530   307272   46295     1447     14     0      2     0   英国   欧洲\n",
       "3    595501  1964536   40699  1328336  56282   904  46121     0   印度   亚洲"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##全球各国昨日'累计死亡'人数前5的国家数据\n",
    "world_country_data.reindex(world_country_data['累计死亡'].sort_values(ascending=False).index)[:5]\n",
    "###累计死亡最多的国家是北美洲的美国，累计死亡人数为2540137人\n",
    "###累计死亡人数前五的国家依次是美国，巴西，墨西哥，英国，印度，说明在海外，疫情并未得到有效的控制和治疗，各国的累计死亡人数较多。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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